2379 Data Scientist Jobs - Page 34

Job Description – Data Scientist Company: Tata Digital Private Limited Tata Digital is a future-ready company focused on building consumer-centric, high-engagement digital products. Our flagship offering, Tata Neu , is a super-app that integrates various consumer services, including groceries, fashion, electronics, travel, financial services, and more, into a seamless experience. As a wholly owned subsidiary of Tata Sons Private Limited , we are committed to driving digital transformation at scale. Role Details Role Title: Data Scientist / Machine Learning Engineer Function: Data Science Location: Bangalore Experience: 3-5 Y About the Role: We are looking for an experienced Data Scientist / Machine Learning Engineer to join our team and help drive innovation in search, recommendation, and ads. You will be responsible for designing, building, and optimizing ML models that enhance user experience and business outcomes at scale. If you have a strong background in developing scalable ML solutions within a product-driven company, we want to hear from you. Key Responsibilities: Develop and optimize ML models for search ranking, recommendations, and ad targeting to improve engagement and monetization. Design, implement, and deploy large-scale ML pipelines in production environments. Experiment with and improve deep learning, NLP, for personalization and relevance. Conduct A/B testing and data-driven evaluations to measure the impact of ML models. Optimize infrastructure and data processing for high-scale real-time and batch ML systems. Stay up to date with advancements in ML, AI, and big data technologies and apply them to business problems. Minimum Qualifications: 3+ years of experience in Data Science / Machine Learning Engineering, with a focus on search, recommendation systems, or advertising. Strong programming skills in Python, Scala, or Java with experience in ML frameworks like TensorFlow, PyTorch, or Scikit-learn . Experience with big data technologies (e.g., Spark, Hadoop, Kafka) and distributed computing. Proficiency in SQL and NoSQL databases for large-scale data processing. Hands-on experience in deploying ML models in production at scale (MLOps, CI/CD for ML). Strong understanding of ranking models, deep learning, NLP, and reinforcement learning. Preferred Qualifications: Familiarity with vector search, embeddings, and retrieval-based models. Strong problem-solving skills and ability to work in a fast-paced environment Experience with cloud platforms like AWS, GCP, or Azure . If you’re passionate about building intelligent, scalable, and high-impact ML solutions, apply now! Learn more about Tata Digital: Tata Neu Tata Digital Newsroom LinkedIn YouTube

Role & responsibilities Collaborate with business areas within Asset Management to identify opportunities for enhancing commercial performance and operational efficiency using Analytics and Data Science. Engage with the Data Architecture function to ensure optimal data sources are used in your analytics and data science projects. Design and implement data engineering pipelines for data retrieval and transformation. Create insightful visualisations to share the findings from your analytical work with stakeholders. Develop Artificial Intelligence / Machine Learning models to address different business problems ranging from client retention, risk monitoring, and global portfolio management tasks. Act as a champion for data science, guiding business users and other analysts on analytical techniques, tools, and technologies. Preferred candidate profile Proficiency in Python, PySpark, R, and SQL programming languages. Knowledge of visualisation tools like Tableau (preferred), Qlik, or Power BI. Hands-on experience with Machine Learning using platforms like Jupyter Notebooks. Experience with cloud service providers like Google Cloud, AWS, and Microsoft Azure. Strong analytical skills, with an ability to bring structure and clarity to poorly-defined problems. Stellar interpersonal skills, with an ability to develop strong relationships with stakeholders.

About the role Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). You will be responsible for Please refer "You will be responsible for " You will need Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). Whats in it for you? Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). About Us As one of the world’s largest retailers and the largest private employer in the United Kingdom (second largest after the UK government) Tesco serves millions of customers a week in our stores and online portal. Tesco Bengaluru is the only international technology and retail operations centre for Tesco worldwide – we make the Tesco experience better for millions of our customers and simpler for over 4,60,000 colleagues around the world. Established in 2004, Tesco Bengaluru is pivotal to Tesco, and we enable its business with our expertise in technology, business operations, property, finance and commercial services.

Job Title: AI/ML Developer – Data Science Shift Timings: 11 am to 8pm[Flexible] About Us: We as Primotech are as an IT Global Solutions company. We’ve been delivering software development and IT projects from several big enterprises to small and medium-sized businesses. We blend agile methodologies with technical expertise to take business to the next level. What We Are Looking for: A skilled Chatbot Developer who specializes in leveraging Large Language Models (LLMs) and Langchain technology to create cutting-edge chatbots. The ideal candidate will be responsible for designing, developing, and deploying chatbots that demonstrate advanced language understanding and natural conversation capabilities. You will collaborate with cross-functional teams to integrate chatbots into various applications and platforms, ensuring seamless user experiences and effective communication channels. Responsibilities: 1. Design and develop chatbots using Large Language Models (LLMs) and Langchain technology. 2. Implement natural language processing (NLP) algorithms to enhance chatbot understanding and responsiveness. 3. Customize, Integrate and Optimize chatbots functionalities to meet specific requirements and use cases. 4. Implement RAG and train the LLMs using LoRA or Q-LoRA. 5. Handle vector database like ChromaDB and Pinecone 6. Conduct thorough testing and debugging applications and updated with the latest advancements in LLMs, NLP, and chatbot technologies. 7. Collaborate with stakeholders to gather requirements and refine application features. 8. Provide technical support and troubleshooting assistance for deployed chatbots. 9. Document design specifications, implementation details, and user guides. Skill Set: 1. Proficiency in Python programming languages . 2. Strong understanding of natural language processing (NLP) techniques and ML algorithms. 3. Experience with Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer), LLAMA or gemini models. 4. Able to implement RAG and train LLMs using LoRA and q-LoRA 5. Create and update vector database. 6. Knowledge of Langchain technology and its applications in chatbot development. 7. Experience with API integration and web services. 8. Excellent problem-solving skills and attention to detail. 9. Strong communication and collaboration skills, with the ability to work effectively in cross functional teams. Interested candidates may share their resume at [email protected] Job Type: Full-time Pay: ₹45,000.00 - ₹85,000.00 per month Benefits: Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Performance bonus Education: Bachelor's (Preferred) Experience: Python: 3 years (Required) ML Engineering Tools: 3 years (Preferred) Stored Procedures: 3 years (Preferred) Generative Ai: 3 years (Preferred) Language: English (Required) Work Location: In person Expected Start Date: 01/07/2025

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role: In this role, you will lead a workstream solutions for complex, ambiguous and high-visibility business challenges. You will set and execute on a vision that reflects your deep analytical expertise. You will be a thought partner to Marketing leadership teams. Meet our team: Our Marketing Analytics transformation is in full swing. We embarked on a path of transforming and building a world class Marketing Analytics Org recently. Our team helps to power PayPal’s high growth Marketing organization by delivering actionable insights and business intelligence to Consumer Marketing Org for our 200+ million customers. Job Description: Your way to impact: You will partner with these teams to understand the insights they require to manage and grow their business and leverage cross-functional teams to develop and land solutions that meet their needs at scale. You are deeply curious and persistent in gaining knowledge about our products and go-to-market strategy. You will have exposure and visibility to PayPal Sales, Product, Finance & Market Insights teams, as you work with them to create a holistic solution to Marketing problems. We are a team of entrepreneurial, enthusiastic, and client-focused members. Your day to day: The successful candidate will be responsible for providing data-driven insights including but not limited to Business casing, Deep dives, Modelling, Campaign Performance readouts and optimisation. The candidate will also be responsible for delivering accurate, action driving recommendations to drive business performance and investment optimisation Manage multiple analytical projects at a time, in a fast-paced, intense, and results-oriented environment Influence stakeholders to make business decisions in alignment with global measurement approaches What do you need to bring: Degree in Statistics, Mathematics, Applied Mathematics, Computer Science, Operations Research, Engineering, Economics 2+ years of experience in analytics, data science or management consulting or equivalent analytical and project management experience Hands on experience of Python, SQL & BigQuery Accomplished Contributor, with experience managing high-performing Data Scientists and Quantitative Analysts Experience working within and driving strategy for large, global, complex organizations across multiple stakeholders and teams Exceptional problem-solving skills, with strong ability to drive towards action and impact Experience in managing analytics projects from inception to delivery, including developing structured solutions Experience with visualizations, dashboards, and reports Experience with data modelling, machine learning algorithms, and data science techniques. Experience explaining technical concepts and analysis implications to varied audiences and translating business objectives into analyses ** We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [email protected] . Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

About the role Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). You will be responsible for Please refer "You will be responsible for " You will need Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). Whats in it for you? Job Description At Tesco; our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores; online; supply chain; marketing and Clubcard; where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects. We work on several domains and problem types: online; pricing; security; fulfilment; distribution; property; IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore; we have a great work-life balance; team days and relaxed but engaging culture. ROLE DESCRIPTION This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist; you will need to understand difficult business problems and prototype solutions with minimal support. Apply; modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop; Spark) is a core component of the role. Our data scientists will need to be able to validate; document and present the modeling process and performances; as well as communicate complex solutions in a clear; understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community. CANDIDATE DESCRIPTION We are looking for ambitious individuals with a mix of statistics; programming; and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential. An ideal candidate will have a scientific mentality with the ability to ask the right questions; as well as answer them. A strong numerical higher degree in a mathematical; scientific; engineering or computer science discipline is preferable; as well as a solid understanding of mathematics and statistical principles. Experience in one or more of the following fields is required: predictive modelling; operational research; deep learning; and time series modelling. Finally; strong programming experience (Python is preferred). About Us As one of the world’s largest retailers and the largest private employer in the United Kingdom (second largest after the UK government) Tesco serves millions of customers a week in our stores and online portal. Tesco Bengaluru is the only international technology and retail operations centre for Tesco worldwide – we make the Tesco experience better for millions of our customers and simpler for over 4,60,000 colleagues around the world. Established in 2004, Tesco Bengaluru is pivotal to Tesco, and we enable its business with our expertise in technology, business operations, property, finance and commercial services.

Day-to-day Responsibilities: Designing and Building machine learning systems based on business requirements and objectives. Research and implement appropriate ML algorithms and tools Perform exploratory data analysis to identify patterns, trends, and correlations in large datasets. Solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward. Responsible for deploying and managing machine learning models in production and ensure their scalability and efficiency. Training and testing ML models at scale in the cloud. Monitor and evaluate model performance, making necessary adjustments to improve accuracy and efficiency. Stay updated with the latest developments in machine learning and AI to bring innovative solutions to the team. Skills And Qualifications 5+ years of experience implementing and deploying machine learning and deep learning frameworks. Strong proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras Experience in productionizing ML Models Experience with natural language processing (NLP) algorithm Experience with containerization technologies (e.g., Docker) Solid understanding of statistical methods and data analysis Solid understanding of LLMs, Prompt Engineering, RAG, GraphRAG, Langchain frameworks. Solid understanding of machine learning algorithms, data structures, and software engineering principles. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their ML services Experience with version control systems like Git, Bitbucket etc Ability to work independently and proactively find solutions to challenges. Ability to collaborate effectively with team members and stakeholders.

JD for Data Scientist Job Title: Data Scientist Job Location: Jaipur Experience: 3 to 6 years Job Description: We are seeking a highly skilled and innovative Data Scientist to join our dynamic and forward-thinking team. This role is ideal for someone who is passionate about advancing the fields of Classical Machine Learning, Conversational AI, and Deep Learning Systems, and thrives on translating complex mathematical challenges into actionable machine learning models. The successful candidate will focus on developing, designing, and maintaining cutting-edge AI-based systems, ensuring seamless and engaging user experiences. Additionally, the role involves active participation in a wide variety of Natural Language Processing (NLP) tasks, including refining and optimizing prompts to enhance the performance of Large Language Models (LLMs). Key Responsibilities: • Generative AI Solutions: Develop innovative Generative AI solutions using machine learning and AI technologies, including building and fine-tuning models such as GANs, VAEs, and Transformers. • Classical ML Models: Design and develop machine learning models (regression, decision trees, SVMs, random forests, gradient boosting, clustering, dimensionality reduction) to address complex business challenges. • Deep Learning Systems: Train, fine-tune, and deploy deep learning models such as CNNs, RNNs, LSTMs, GANs, and Transformers to solve AI problems and optimize performance. • NLP and LLM Optimization: Participate in Natural Language Processing activities, refining and optimizing prompts to improve outcomes for Large Language Models (LLMs), such as GPT, BERT, and T5. • Data Management & Feature Engineering: Work with large datasets, perform data preprocessing, augmentation, and feature engineering to prepare data for machine learning and deep learning models. • Model Evaluation & Monitoring: Fine-tune models through hyperparameter optimization (grid search, random search, Bayesian optimization) to improve performance metrics (accuracy, precision, recall, F1-score).Monitor model performance to address drift, overfitting, and bias. • Code Review & Design Optimization: Participate in code and design reviews, ensuring quality and scalability in system architecture and development. Work closely with other engineers to review algorithms, validate models, and improve overall system efficiency. • Collaboration & Research: Collaborate with cross-functional teams including data scientists, engineers, and product managers to integrate machine learning solutions into production. Stay up to date with the latest AI/ML trends and research, applying cutting-edge techniques to projects. Qualifications: • Educational Background: Bachelors or Masters degree in Computer Science, Mathematics, Statistics, Data Science, or any related field. • Experience in Machine Learning: Extensive experience in both classical machine learning techniques (e.g., regression, SVM, decision trees) and deep learning systems (e.g., neural networks, transformers). Experience with frameworks such as TensorFlow, PyTorch, or Keras. • Natural Language Processing Expertise: Proven experience in NLP, especially with Large Language Models (LLMs) like GPT, BERT, or T5. Experience in prompt engineering, fine-tuning, and optimizing model outcomes is a strong plus. Programming Skills: Proficiency in Python and relevant libraries such as NumPy, Pandas, Scikit-learn, and natural language processing libraries (e.g., Hugging Face Transformers, NLTK, SpaCy). • Mathematical & Statistical Knowledge: Strong understanding of statistical modeling, probability theory, and mathematical optimization techniques used in machine learning. • Model Deployment & Automation: Experience with deploying machine learning models into production environments using platforms such as AWS SageMaker or Azure ML, GCP AI, or similar. Familiarity with MLOps practices is an advantage. • Code Review & System Design: Experience in code review, design optimization, and ensuring quality in large-scale AI/ML systems. Understanding of distributed computing and parallel processing is a plus. Soft Skills & Behavioural Qualifications: • Must be a good team player and self-motivated to achieve positive results • Must have excellent communication skills in English. • Exhibits strong presentation skills with attention to detail. • Its essential to have a strong aptitude for learning new techniques. • Takes ownership for responsibilities • Demonstrates a high degree of reliability, integrity, and trustworthiness • Ability to manage time, displays appropriate sense of urgency and meet/exceed all deadlines • Ability to accurately process high volumes of work within established deadlines. Thanks & Regards Sulabh Tailang HR-Talent Acquisition Manager |Celebal Technologies |91-9448844746 Sulabh.tailang@celebaltech.com|LinkedIn-sulabhtailang |Twitter-Ersulabh Website-www.celebaltech.com

Job Title Data Scientist Predictive Analytics & Machine-Learning Solutions Location : Business Unit: Business Intelligence Why this role exists Fusion Business Solutions (P) Ltd. helps clients turn operational data into competitive advantage. As a Data Scientist you will design and deliver predictive models, machine-learning pipelines and data-driven insights that accelerate decision-making for both internal stakeholders and external customers. What you will do: Translate high-level business goals into data questions and measurable success criteria. Acquire, clean and combine large structured and unstructured datasets; document assumptions and data-quality checks. Explore data to uncover patterns, drivers and anomalies; present findings through clear visual stories and executive briefs. Build, validate and tune forecasting, classification, regression, recommendation and clustering models with modern open-source libraries. Package models for production with reproducible code, versioned artefacts and automated tests; deploy via REST APIs, batch jobs or embedded BI dashboards. Monitor accuracy, drift and usage; schedule retraining or rollback when thresholds are breached. Collaborate with data engineers on pipeline design and with BI developers on dashboard integration. Advise on A/B-test design and causal-impact analysis. Coach analysts and junior team members in statistical thinking, coding best practices and responsible AI principles. Technology you are likely to touch Python (pandas, scikit-learn, PyTorch/TensorFlow) SQL Spark or PySpark Docker, MLflow (or similar) Airflow/DBT GitHub Actions Power BI (or equivalent) At least one major cloud environment (AWS, GCP or Azure) Familiarity with generative-AI frameworks, NLP libraries or computer-vision toolkits is a plus. Must-have qualifications Three or more years of hands-on experience building and deploying predictive-analytics or machine-learning solutions that delivered measurable business value. Strong SQL skills and experience modelling datasets larger than 100 GB. Proficiency in Python (or R) for data analysis, modelling and automation. Practical understanding of model lifecycle management—including experiment tracking, version control, containerisation and CI/CD. Ability to explain technical concepts to non-technical audiences and to write concise technical documentation. Good-to-have extras Insurance domain exposure —experience working with policy, claims, premium or commission data; familiarity with underwriting or fraud-detection use cases; understanding of regulatory frameworks such as HIPAA, NAIC or IFRS 17. Experience in other FBSPL focus areas—accounting/BFSI workflows (general ledger, AP/AR), e-commerce fulfilment, RPA-driven back-office processes, or data-annotation quality control. Cloud-native ML services (AWS SageMaker, Google Vertex AI, Azure ML) and MLOps best practices. Time-series forecasting, optimisation algorithms or deep-learning frameworks. Certifications such as AWS Machine Learning Specialty, Microsoft DP-100, UiPath RPA Developer, or equivalent.

Job Summary We are seeking highly skilled and motivated Data Scientists to join our dynamic team. The ideal candidate will be responsible for designing and implementing data-driven solutions that inform strategic decisions, improve customer experience, and drive business growth. Key Responsibilities Develop, test, and deploy predictive models and machine learning algorithms to solve business problems. Analyze large, complex datasets to extract actionable insights and trends. Collaborate with cross-functional teams (engineering, product, marketing, operations) to understand business requirements and deliver data solutions. Communicate findings and recommendations to stakeholders through visualizations, presentations, and reports. Build and maintain dashboards and analytical tools for ongoing monitoring and reporting. Clean, preprocess, and manage data pipelines for modeling and analytics. Evaluate model performance and continuously improve based on feedback and new data. Stay current with the latest developments in data science, machine learning, and analytics technologies. Requirements Education: Bachelors or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Experience: Professional experience in data science, analytics, or a related field. Technical Skills: Strong programming skills in Python and/or R. Proficiency in SQL for data extraction and manipulation. Experience with machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Experience with cloud platforms (e.g., AWS, GCP, Azure) is a plus. Knowledge of statistical techniques and their practical applications. Soft Skills: Excellent analytical and problem-solving skills. Strong communication and collaboration skills. Ability to work independently and manage multiple tasks and projects. Preferred Qualifications Experience with big data technologies (e.g., Spark, Hadoop). Knowledge of A/B testing and experiment design. Exposure to CI/CD practices and version control (e.g., Git). Experience working in an agile development environment.

LocationHyderabad Job model Hybrid Purpose of the job We are looking for a highly analytical and detail-oriented Data Scientist to join our Data Quality Management team This role will focus on ensuring the accuracy, completeness, and reliability of data ingested from SAP systems and logistics carriers You will play a critical role in enhancing the integrity of our transportation visibility platform by identifying data issues, implementing quality controls, and collaborating with cross-functional teams to resolve data discrepancies At dsm-firmenich, being a force for good is not optional Diversity, Equity & Inclusion is a shared responsibility woven into our daily work to not only benefit our People, Cusotmers & Communities but also drive business value Equal access to opportunities is a given, belonging is a shared feeling, authencity is celebrated Key Responsibilities Design and implement data quality frameworks and monitoring systems for SAP and carrier data pipelines Analyze large datasets to detect anomalies, inconsistencies, and gaps in data quality Experience working on TransVoyant Develop automated data validation and cleansing routines using Python, SQL, and other tools Create dashboards and reports to communicate data quality metrics and trends Collaborate with functional experts, business analysts, and domain experts to understand data flows and business rules Work closely with Logistics operations, business units, SAP data entry functions, and carrier integration partners to resolve data issues at the source Contribute to the development of data governance policies and best practices We bring The opportunity to work for a company where sustainability is much more than a claim and is core to our strategy and purpose A flexible work environment that empowers people to take accountability for their work and own the outcome An eagerness to be one team and learn from each other to bring progress to life and create a better future Barrier-free communities within our organization where every employee is equally valued and respected regardless of their background, beliefs, or identity A culture that prioritizes safety and well-being, both physically and mentally A space to grow by encouraging and supporting curiosity and an open mindset You bring Bachelors or masters degree in data science, Computer Science, Information Systems, or a related field 5+ years of experience in data science, data engineering, or data quality roles Strong experience working with SAP data structures (e g , SD, MM, WM modules) and carrier logistics data (e g , EDI, shipment tracking) Proficiency in SQL, Python, and data visualization tools (e g , Power BI, Tableau) Experience with real-time data processing and streaming technologies Knowledge and experience with SQL and cloud database systems such as AWS or CGP Comfortable using Microsoft Excel to analyze and summarize data, including graphs, charts, formulas, functions, solvers, and regression analysis Able to identify trends, patterns, and outliers in logistics data and form insights and recommendations Ability to work in a fast-paced environment while managing multiple projects/priorities simultaneously Excellent attention to detail, problem-solving, organizational and prioritization skills Strong communication skills to collaborate effectively with cross-functional teams and present findings to both technical and non-technical audiences Knowledge of supply chain, transportation and logistics operations is a plus The application process Interested in this positionPlease apply on-line by uploading your resume in English via our career portal For further information, please contact Kubra Ali Khan, Talent Acquisition (kubra ali-khan@dsm-firmenich com) Equal Opportunities Commitment dsm-firmenich is fully dedicated to inclusion because when people feel engaged and empowered, their creativity and innovation drives unprecedented progress We aim to build a workplace where opportunity really is equal, so everyone can thrive We do not discriminate: there's a place for everyone at dsm-firmenich As a committed equal opportunity employer, we ensure our recruitment practices are inclusive and fair We encourage the recruitment of a diverse worforce, representative of the communities in which we work, by using inclusive language, diverse interview panels, diversified sourcing strategies Selection is based on qualifications, competency, experience, performance history and fit with the team to advance fair and equitable opportunity Employment decisions are based upon job-related reasons regardless of an applicant's race, color, ethnicity,national origin, religion, gender, gender identity or expression, sexual orientation, age, disability, backgrounds ,genetic information, protected veteran status, or any other status protected by law We are committed to providing reasonable support for disabled applicants in our recruiting process Should you need assistance , and are comfortable to share this, please let us know About Dsm-firmenich As innovators in nutrition, health, and beauty, dsm-firmenich reinvents, manufactures, and combines vital nutrients, flavors, and fragrances for the worlds growing population to thrive With our comprehensive range of solutions, with natural and renewable ingredients and renowned science and technology capabilities, we work to create what is essential for life, desirable for consumers, and more sustainable for the planet dsm-firmenich is a Swiss-Dutch company, listed on the Euronext Amsterdam, with operations in almost 60 countries and revenues of more than 12 billion With a diverse, worldwide team of nearly 30,000 employees, we bring progress to lifeevery day, everywhere, for billions of people Agency Statement Please note this is a direct search led by dsm-firmenich We only accept applications from candidates, not from agencies nor subject to agencys fees, percentages or similar

Job Description Job Profile - Lead, Data Scientist We are looking for a passionate ML /AI Lead Data Scientist with demonstrated thought-leadership & proven ability to lead the development of analytics-focused products and utilizing cutting edge machine learning, natural language processing, and mathematical techniques to drive powerful business results. You will have the opportunity to work with a wide range of stakeholders and functional teams to help them discover insights hidden in data sets and enable stakeholders to improve business. AI ethics, fairness and secure development practices are also our focus areas. Responsibilities Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem Collaborate & share best practices with data and software engineers to enable consistent deployment of high-quality models that will scale across the company s ecosystem Own the code review process to ensure stringent coding guidelines are met by other data scientists & data engineers Mentor & lead Data Science engineers in choosing the right machine learning approach/ models & utilizing open source languages such as R, Python, etc. Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to non-technical audience in a simple and clear manner Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric Build frameworks leveraging APIs to industrialize AI models across the organization Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Requirements and Skills You should have bachelor s or Master s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field You should have experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory. In depth understanding of NLP, LLM, Generative AI, RAG application development. In-depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc. Fluency in programming skills such as Python, R, or other equivalent languages Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is desirable Experience working with Amazon SageMaker or Azure ML Studio for deployments is required Experience in data visualization software such as Tableau, ELK, etc is a plus Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners About Us Schneider Electric creates connected technologies that reshape industries, transform cities and enrich lives. Our 144,000 employees thrive in more than 100 countries. From the simplest of switches to complex operational systems, our technology, software and services improve the way our customers manage and automate their operations. Help us deliver solutions that ensure Life Is On everywhere, for everyone and at every moment: Great people make Schneider Electric a great company. We seek out and reward people for putting the customer first, being disruptive to the status quo, embracing different perspectives, continuously learning, and acting like owners. We want our employees to reflect the diversity of the communities in which we operate. We welcome people as they are, creating an inclusive culture where all forms of diversity are seen as a real value for the company. We re looking for people with a passion for success on the job and beyond. Qualifications Responsibilities Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization Coordinate with business teams to monitor outcomes and refine/ improve the machine learning models Work across the spectrum of statistical modelling including supervised, unsupervised, & deep learning techniques to apply the right level of solution to the right problem Collaborate & share best practices with data and software engineers to enable consistent deployment of high-quality models that will scale across the company s ecosystem Own the code review process to ensure stringent coding guidelines are met by other data scientists & data engineers Mentor & lead Data Science engineers in choosing the right machine learning approach/ models & utilizing open source languages such as R, Python, etc. Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to non-technical audience in a simple and clear manner Track emerging developments w.r.t technology, tools, practices, etc in the open source, data science/machine learning/chatbot domain and leverage same for Schneider Electric Build frameworks leveraging APIs to industrialize AI models across the organization Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Requirements and Skills You should have bachelor s or Master s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field You should have 7+ years of experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory. In depth understanding of NLP, LLM, Generative AI, RAG application development. In-depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required Knowledge of vector algebra, statistical and probabilistic modelling is highly desirable Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus Experience in major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML etc. Fluency in programming skills such as Python, R, or other equivalent languages Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is desirable Experience working with Amazon SageMaker or Azure ML Studio for deployments is required Experience in data visualization software such as Tableau, ELK, etc is a plus Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners Schedule: Full-time Req: 009G5J

Build cutting edge models using NLP, ML and AI Techniques for a variety of problems in a variety of domains. Work with engineering team to deploy models in production & validate the models. Expert level knowledge in Natural Language Processing, Information Extraction, Scrapping and Text Mining Algorithms, Tech Stacks. Strong familiarity with deep learning methods for text analytics. Expert level knowledge in Machine Learning algorithms (XGBoost, Linear and Logistic Regression, SVM, Random Forest, Bayesian Methods, Unsupervised Learning, Reinforcement Learning) is a must. Familiarity and experience of working on time series analysis on real world datasets. Familiarity with flask, fastapi, hug. Must be an expert python programmer. Demonstrated expertise via high quality publications and/or competitions/challenges. Ability to easily work with domain experts and passion to make a difference. Minimum B.E/B.Tech in computer science/ Electrical Engineering/ EXTC with a strong base in mathematics and statistics. Strong communication skills and team player. Ability to thrive in a startup environment. Problem solving attitude is a must. Desired Candidate Profile Data Scientist to join team and completely take care of Text Analytics on Qualitative Customer Feedback and Call Center complaints conversations via Email or Chat.

Being part of and contributing to a large, vibrant community Understanding problems and designing solutions for the P&C Insurance industry. Applying a variety of analytic methodologies including Predictive Modeling, Machine Learning, Forecasting, Network Analytics, Natural Language Processing, Computer Vision, Voice and Speech Analytics, and Generative AI to develop solutions to those business problems Working with a diverse set of extremely rich datasets such as 19 billion detailed records of insurance premiums collected and losses paid, or 90%+ of Insurance Claims in the US Seeing your work result in new products, product enhancements, consulting revenue, or internal process improvements on a regular basis Working with cutting-edge technology, and continuously developing new skills and capabilities. A degree in a quantitative field with relevant experience: Bachelors (3-5 years) or Masters (1-2 years), or PhD (0-2 years). Strong programming skills, particularly in R and Python. Extensive experience in one or more of the following skills is essential: Predictive Modeling, Entity Resolution, NLP, and Generative AI. Experience in any of the following skills is a plus: Big Data Platforms, Time-Series Forecasting, Graph Databases, Network Analytics, Neural Networks, Computer Vision, and ASR (Automated Speech Recognition). Familiarity with SQL or NoSQL (eg, Hadoop, HBase, MongoDB and/or Neo4j) databases. Domain knowledge in the insurance industry is an added advantage. Ability to solve problems analytically and creatively. Strong communication (written and oral) skills. The development and timely delivery of analytic solutions that meet business requirements around accuracy, sophistication, and interpretability. Develop analytic solutions using machine learning techniques including Predictive Modeling, Text Mining, Entity Resolution, Time-series Forecasting, Network Analytics, Computer Vision, Automated Speech Recognition, and Generative AI. Ensure that solutions meet business requirements around accuracy, sophistication, and interpretability. Ensure that solution is delivered in a timely manner. The incorporation of technical innovations and new developments in relevant analytic fields Keep abreast of technical innovations and new developments in relevant analytic fields The development of analytic interns that you are responsible for Identify training opportunities and project opportunities that can help develop the analytic interns you are responsible for The sharing of important methodologies, advances, and best practices from your work among the whole analytic community Help organize these forums for developing Verisk s analytic community Share important methodologies, advances, and best practices from your work among the whole analytic community via these forums. Success Criteria: Measurable contribution to products and processes in terms of new products developed, enhanced products, direct revenue supported, cost savings etc Positive feedback on the support received from business partners Advancement of analytic interns that you are responsible for Positive feedback from analytic interns that you are responsible for Positive feedback from team members and leaders of the Verisk analytic community

We are looking for a Staff Data Scientist to join our Silicon Verification Data Science team. In this role, you will use advanced data science, AI/ML techniques to drive efficiency, automation, and innovation in Silicon Design Verification. You will work closely with hardware engineers, verification teams, and software developers to optimize verification workflows, improve coverage, and accelerate time-to-market for cutting-edge semiconductor products. As a Staff Engineer/ Data Scientist at Micron, you will Develop AI and Data Science based solutions to build state-of-the-art solutions for silicon design verification and firmware validation. Identify patterns, anomalies, and inefficiencies in silicon design verification processes and develop solutions to address these gaps. Automate data pipelines and develop tools to support regression analysis, bug triaging, and root cause analysis. Partner with cross-functional teams to integrate data-driven solutions into EDA tools and verification frameworks. Drive technical innovation and culture within the team by participating in generating IP and inspiring team to innovate. Participate in end-to-end project scoping and stakeholder discussions to determine technical merit of the idea, vale proposition and resource requirements. Interact with subject matter experts to define scope, identify risks, deploy scalable solutions & lead multiple projects execution Continuously learn as we'll as mentor team on recent progress on semiconductor and AI/ML domain. Key requirements: Education: masters or PhD in Computer Science, Electrical Engineering, or a related field. Experience: 8+ years in data science and machine learning with at least 2 years in semiconductor verification environment Technical Skills In-depth understanding of Statistics, classical ML and deep learning, and the mathematics and formulation behind these algorithms. we'll versed with text processing, various methodologies in data embedding, NLP techniques and recent advancements in GenAI and LLMs. Hands-on experience with optimization and reinforcement learning based algorithms. Solid understanding of data engineering pipeline for deployment and MLOps. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks (eg, TensorFlow, PyTorch) and data visualization tools (eg, Tableau, Power BI). Strong understanding of digital design and verification concepts (eg, RTL, UVM, coverage metrics, simulation). Experience with EDA tools (eg, Synopsys VCS, Cadence Xcelium, Mentor Questa) and verification flows is a great plus. Preferred Qualifications: Knowledge of hardware description languages (Verilog/SystemVerilog). Experience with CI/CD pipelines and MLOps practices. Patents or publications in relevant fields.

Responsible for conducting in-depth analysis of complex datasets, deploying predictive models, applying optimization techniques, designing decision support systems, analyzing experiments, collaborating with cross-functional teams, staying abreast of advancements, and assessing the impact of data-driven decisions. Grade - T2 What your main responsibilities are: 1. Conduct in-depth analysis of complex data sets to uncover actionable insights and trends. 2. Develop and deploy predictive models to forecast business outcomes and support decision-making processes. 3. Apply optimization techniques to improve business processes and resource allocation. 4. Design and implement decision support systems that enable stakeholders to make data-driven decisions. 5. Design and analyze experiments to evaluate the effectiveness of business strategies and interventions. 6. Collaborate with cross-functional teams and stakeholders to understand business requirements and priorities. 7. Stay abreast of advancements in data science, machine learning, and decision science to enhance analytical capabilities. 8. Assess the impact of data-driven decisions on key business metrics and outcomes and iterate on models and strategies accordingly. What we are looking for Education: Bachelors degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline. Masters degree or PhD is preferred. Relevant work experience in decision science based on the following number of years: Standard I: Two (2) years Standard II: Three (3) years Senior I: Four (4) years Senior II: Five (5) years Knowledge, Skills and Abilities Fluency in English Analytical Skills Accuracy & Attention to Detail Numerical Skills Planning & Organizing Skills Presentation Skills Statistical and Mathematical Knowledge Data Modeling and Visualization Skills Programming Skills

Job Title: Data Scientist AI/ML, Generative AI & Databricks Experience: 2-3 Years; 3-5+ Years Employment Type: Full-Time Job Description: We are seeking a highly skilled and experienced Senior Data Scientist who thrives at the intersection of Machine Learning, Generative AI, and Cloud-native MLOps. The ideal candidate will have hands-on experience building end-to-end AI/ML models, working with Large Language Models (LLMs), deploying solutions at scale, and leveraging the full potential of the Databricks ecosystem. Responsibilities: Design, build, and deploy scalable machine learning and AI models using Databricks, from ideation to production. Develop and fine-tune Generative AI and LLM-based solutions for use cases such as summarization, text generation, and synthetic data generation. Drive MLOps best practices using tools like MLflow, Delta Lake, and Unity Catalog for model versioning, reproducibility, and governance. Collaborate with product managers, data engineers, and other data scientists to deliver impactful solutions to business problems. Optimize model performance, conduct error analysis, and ensure efficient cloud resource utilization in Azure or AWS environments. Lead technical discussions, code reviews, and mentor junior data scientists within the team. Stay abreast of the latest research and trends in AI/ML and proactively apply them to real-world use cases. Communicate technical findings clearly to both technical and non-technical stakeholders. Qualifications: Bachelors or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in applied data science, AI, and machine learning. Proven expertise in developing ML models from scratch, including preprocessing, feature engineering, and model tuning. Hands-on experience with LLMs and Generative AI (e.g., GPT, LLaMA, Falcon, etc.) and fine-tuning domain-specific models. Advanced programming skills in Python, with experience in relevant ML libraries (e.g., scikit-learn, PyTorch, TensorFlow). Deep familiarity with the Databricks platform: Delta Lake, Agent Bricks, Unity Catalog, MLflow, Mosaic AI, and integration with cloud ecosystems (Azure/AWS). Solid understanding of MLOps principles, CI/CD pipelines, and production-level deployments. Excellent communication and interpersonal skills with the ability to simplify complex concepts.

Join our Team About This Opportunity The complexity of running and optimizing the next generation of wireless networks, such as 5G with distributed edge compute, will require Machine Learning (ML) and Artificial Intelligence (AI) technologies Ericsson is setting up an AI Accelerator Hub in India to fast-track our strategy execution, using Machine Intelligence (MI) to drive thought leadership, automate, and transform Ericssons offerings and operations We collaborate with academia and industry to develop state-of-the-art solutions that simplify and automate processes, creating new value through data insights What You Will Do As a Senior Data Scientist, you will apply your knowledge of data science and ML tools backed with strong programming skills to solve real-world problems Responsibilities: Lead AI/ML features/capabilities in product/business areas Define business metrics of success for AI/ML projects and translate them into model metrics Lead end-to-end development and deployment of Generative AI solutions for enterprise use cases Design and implement architectures for vector search, embedding models, and RAG systems Fine-tune and evaluate large language models (LLMs) for domain-specific tasks Collaborate with stakeholders to translate vague problems into concrete Generative AI use cases Develop and deploy generative AI solutions using AWS services such as SageMaker, Bedrock, and other AWS AI tools Provide technical expertise and guidance on implementing GenAI models and best practices within the AWS ecosystem Develop secure, scalable, and production-grade AI pipelines Ensure ethical and responsible AI practices Mentor junior team members in GenAI frameworks and best practices Stay current with research and industry trends in Generative AI and apply cutting-edge techniques Contribute to internal AI governance, tooling frameworks, and reusable components Work with large datasets including petabytes of 4G/5G networks and IoT data Propose/select/test predictive models and other ML systems Define visualization and dashboarding requirements with business stakeholders Build proof-of-concepts for business opportunities using AI/ML Lead functional and technical analysis to define AI/ML-driven business opportunities Work with multiple data sources and apply the right feature engineering to AI models Lead studies and creative usage of new/existing data sources What You Will Bring Bachelors/Masters/Ph D in Computer Science, Data Science, AI, ML, Electrical Engineering, or related disciplines from reputed institutes 3+ years of applied ML/AI production-level experience Strong programming skills (R/Python) Proven ability to lead AI/ML projects end-to-end Strong grounding in mathematics, probability, and statistics Hands-on experience with data analysis, visualization techniques, and ML frameworks (Python, R, H2O, Keras, TensorFlow, Spark ML) Experience with semi-structured/unstructured data for AI/ML models Strong understanding of building AI models using Deep Neural Networks Experience with Big Data technologies (Hadoop, Cassandra) Ability to source and combine data from multiple sources for ML models Preferred Qualifications: Good communication skills in English Certifying MI MOOCs, a plus Domain knowledge in Telecommunication/IoT, a plus Experience with data visualization and dashboard creation, a plus Knowledge of Cognitive models, a plus Experience in partnering and collaborative co-creation in a global matrix organization Why join Ericsson At Ericsson, you?ll have an outstanding opportunity The chance to use your skills and imagination to push the boundaries of what?s possible To build solutions never seen before to some of the worlds toughest problems You?ll be challenged, but you wont be alone You?ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next What happens once you apply Click Here to find all you need to know about what our typical hiring process looks like Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team Ericsson is proud to be an Equal Opportunity Employer learn more Primary country and city: India (IN) || Bangalore Req ID: 766481

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field 5 years of work experience using analytics to solve product or business problems, coding (e g , Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree Preferred qualifications: 8 years of work experience using analytics to solve product or business problems, coding (e g , Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data About The Job At Google, data drives all of our decision-making Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior As an analyst, you do more than just crunch the numbers You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings Identifying the problem is only half the job; you also figure out the solution The team's mission is to protect Android users from abusive apps, including malware, content abuse, impersonation, and behavioral abuse As a Data Scientist on the App Safety Engineering (ASE) team, you will work with multiple stakeholders across product, engineering, and operation teams to conduct data research, build methodologies into production systems to drive ASE key decisions and development You will be responsible for translating data into recommendations and implementing process improvements Responsibilities Work with datasets, solve non-routine analysis problems, and apply quantitative methods as needed Conduct analysis that includes data gathering and requirements specification, processing, analysis, model development and evaluation, as well as written and verbal delivery of results to business partners Collaborate with stakeholders in Product Management, Engineering, and Operation teams to define questions, objectives, and metrics, identify and implement quantitative methods to answer those questions Develop, own, and evolve methodologies and frameworks providing a source of truth measures for the organization Establish comprehensive understanding of the production systems, advocate for changes where needed for product development, and build data driven solutions to faciliate the efficacy improvement Google is proud to be an equal opportunity workplace and is an affirmative action employer We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status We also consider qualified applicants regardless of criminal histories, consistent with legal requirements See also Google's EEO Policy and EEO is the Law If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience 5 years of work experience with analysis applications (e g , extracting insights, performing statistical analysis, or solving business problems), and coding (e g , Python, R, SQL) (or 2 years work experience with a Master's degree) Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field 5 years of work experience with analysis applications (e g , extracting insights, performing statistical analysis, or solving business problems), and coding (e g , Python, R, SQL) About The Job Help serve Google's worldwide user base of more than a billion people Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions You will weave stories with meaningful insight from data You'll make critical recommendations for your fellow Googlers in Engineering and Product Management You relish tallying up the numbers one minute and communicating your findings to a team leader the next Google One is a subscription to Google that delivers expanded storage, premium features, and AI-powered experiences across Google products to members The team partners with teams across Google to deliver valuable experiences to users that drive engagement for business growth Google Photos is a photo sharing and storage service developed by Google Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers We are dedicated to making Google experiences centered around the user Responsibilities Partner with Product Management, Engineering, and more in Analytics to understand the profile of Google One business, use data to evaluate how business is evolving and drive decisions based on insights Identify business problems and come up with analytical solutions that improve product and user experience Google is proud to be an equal opportunity workplace and is an affirmative action employer We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status We also consider qualified applicants regardless of criminal histories, consistent with legal requirements See also Google's EEO Policy and EEO is the Law If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form

B. Tech / B.E. from a Tier-1 Institution (IITs, IISc, IIITs, BITS, NITs or similar institutions), preferably in Computer Science, IT, Electronics Engineering, Electrical Engineering, Mathematics or any other related field. Minimum 2+ years of hands-on experience in machine learning, deep learning, or computer vision roles. Strong expertise in deep learning frameworks such as PyTorch, TensorFlow, and Keras. In-depth knowledge of CNNs, Transformers, Siamese networks, contrastive learning, and embedding space analysis. Proficient in Python and experienced with largescale data processing tools like Spark, Dask, or Hadoop. Prior experience working with biometric, or image datasets (face, iris, fingerprint) is desirable. • Strong understanding of data cleaning, clustering (e.g., DBSCAN, K-Means), anomaly detection, and unsupervised learning. Knowledge of privacy-preserving techniques such as federated learning, differential privacy & homomorphic encryption is a plus. Job Profile Design and develop state-of-the-art deep learning models for biometric recognition (facial, fingerprint, iris) and fraud detection using convolutional neural networks (CNNs), transformers, and hybrid architectures. Lead the design of end-to-end AI pipelines: data ingestion, pre-processing, model training, evaluation, and deployment in production environments. Conduct thorough error analysis A/B testing, and performance evaluations to identify weaknesses and improve recognition accuracy and system efficiency. Architect scalable data pipelines for image and biometric signal cleaning, feature extraction, clustering, and deduplication at the national scale. Collaborate with domain experts, biometric vendors, and legal/policy teams to ensure technological solutions are interpretable, robust, and policy compliant. Monitor system drift, adversarial threats, and fraud patterns in biometric usage across the Aadhaar ecosystem. Publish internal technical reports and participate in peer reviewed research where appropriate. Mentor and guide junior data scientists and ML engineers in best practices. What We Offer Unique opportunity to work on the largest biometric identity system in the world. Access to UIDAIs unparalleled scale of identity data and secure research environments. Competitive compensation and benefits tailored for top-tier AI talent in the public sector. A mission-driven organization with direct impact on national scale governance, security, and inclusion

Company Description Derangula Consulting Inc. offers business intelligence, IT consultancy & support, and staffing services tailored to meet your business needs. Our team of experts is committed to helping you maximize the benefits of our services and support your business growth. We are seeking a skilled and motivated Data Scientist or Data Engineer with strong proficiency in Python and machine learning to join our growing data team. The ideal candidate will work on designing, building, and deploying scalable data and machine learning pipelines to support decision-making, product development, and strategic initiatives. Key Responsibilities: Design, develop, and prediction analysis with BI solutions. Build, train, and deploy machine learning models to solve prediction. Analyze large datasets to extract actionable insights and support business goals. Implement best practices for data quality, governance, and version control. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Strong proficiency in Python and related libraries (Pandas, NumPy, Scikit-learn, etc.). Hands-on experience with machine learning algorithms and model deployment. Solid knowledge of SQL and relational databases. Preferred Qualifications: Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Exposure to data warehousing solutions (e.g., Snowflake, BigQuery). 1.BI knowledge is must 2.Having any BI tool exp (Qlik, Tableau) If you’re passionate about turning historical data into actionable insights and have a track record of delivering reliable forecasts, we’d love to hear from you Feel free to call us -9390571086 Mail-derangulamahesh61@gmail.com

Building and maintaining systems for extracting, pre- processing and modelling for different data streams, as well as integrating data across different sources. Expertise in visualizations and data analysis. Creating predictive and prescriptive models that could have a positive impact on the business. Integrating data engineering and modelling algorithms/techniques and solutions into the backend systems Develop model monitoring infrastructure for periodic monitoring and upgradation of data science strategies and models Building & implementing state-of-the-art deep learning models. Working with various stakeholders to identify and capitalize on opportunities to leverage data to drive business solutions. R Programming / Python Scripting / SQL; Experience in Finance, R-Studio/Shiny. Experience 5 - 7 Years . Industry IT Software - Application Programming / Maintenance Qualification B.E Key Skills Data Analyst R Programming Python R Programmer

Job Description: Key Responsibilities: Design and develop machine learning and deep learning systems using frameworks like TensorFlow, PyTorch, and Scikit-learn. Implement real-time systems for forecasting, optimization, and personalized recommendations. Research and apply advanced AI/ML techniques, including Generative AI models (e.g., GPT, LLaMA) and NLP architectures. Lead end-to-end machine learning projects, from problem framing to deployment and monitoring. Manage model lifecycle activities, including training, testing, retraining, and fine-tuning for optimal performance. Collaborate with analytics teams, practice leads, subject matter experts, and customer teams to understand business objectives and technical requirements. Conduct statistical analysis to address business challenges and drive innovation in AI/ML applications. Deploy machine learning applications on cloud platforms (e.g., GCP, Azure, AWS) and ensure seamless integration with existing systems. Monitor system performance, address data drift, and ensure scalability and adaptability to evolving requirements. Qualifications: Minimum 7+ years for Principal Data Scientist roles (3+ years for Data Scientist roles) with proven expertise in AI/ML, particularly in Generative AI, NLP, and computer vision. Proficient in Python, Java, and R. Strong expertise in TensorFlow, PyTorch, Scikit-learn, Django, Flask, Numpy, and Pandas. Comprehensive knowledge of data structures, SQL, multi-threading, and APIs (RESTful, OData). Hands-on experience with Tableau and Power BI for data visualization. Strong understanding of statistics, probability, algorithms, and optimization techniques. Experience deploying ML applications on GCP, Azure, or AWS. Familiarity with ERP/SAP integration, post-production support, and lifecycle management of ML systems. Industry experience in retail, telecom, or supply chain optimization is a plus. Exceptional problem-solving skills, strong leadership capabilities, and excellent communication skills.

Position Name: Data Scientist/Lead Data Scientist Job Details: We are seeking a highly motivated and enthusiastic Junior Data Scientist with 5-10 years of experience to join our data science team. This role offers an exciting opportunity to contribute to both traditional Machine Learning projects for our commercial IoT platform and cutting-edge Generative AI initiatives. Experience 5-10 years of hands-on experience with machine learning Exposure to Generative AI concepts and techniques, such as Large Language Models (LLMs), RAG Architecture Experience in manufacturing and with an IoT platform is preferable Role and Responsibilities: Key Objectives Machine Learning (ML): Assist in the development and implementation of machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Help with Python development to integrate models with the overall application Monitor and evaluate model performance using appropriate metrics and techniques. Generative AI: Build Gen AI-based tools for various business use cases by fine-tuning and adapting pre-trained generative models Support the exploration and experimentation with Generative AI models Research & Learning: Stay up-to-date with the latest advancements and help with POCs Proactively research and propose new techniques and tools to improve our data science capabilities. Collaboration and Communication: Work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to understand requirements and deliver impactful solutions. Communicate findings, model performance, and technical concepts to both technical and non-technical audiences. Technical Competencies Programming: Proficiency in Python, with experience in libraries like numpy, pandas, and matplotlib for data manipulation and visualization. ML Frameworks: Experience with TensorFlow, PyTorch, or scikit-learn. Cloud & Deployment: Basic understanding of cloud platforms such as Databricks, Google Cloud Platform (GCP), or Microsoft Azure for model deployment. Data Processing & Evaluation: Knowledge of data preprocessing, feature engineering, and evaluation metrics such as accuracy, F1-score, and RMSE.