2379 Data Scientist Jobs - Page 32

Immediate joiners to max 15 days only Work Location: Hyderabad 5 days work from office No. of positions: 5 Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. Proven experience as a Data Scientist with 4-5 years of hands-on experience. Strong proficiency in Python programming, machine learning model development, and GenAI integration. Expertise in machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Knowledge of MLOps practices, including model versioning and containerization. Excellent data analysis and problem-solving skills with attention to detail. Effective communication and collaboration skills. Data Analytics view , Analytical Thinking, Data Slicing, Data Engineering. Select the right model and present the findings & justification / documentation of the findings - PPT / Other ways of doing Plan his own work / day Additional Preferred Skills: Experience with cloud platforms (e.g., AWS, Azure, GCP). Familiarity with big data technologies (e.g., Apache Spark, Hadoop). Knowledge of deep learning techniques and neural networks. Previous involvement in end-to-end machine learning lifecycle projects with GenAI components If Interested please reach mounika.tungala@coforge.com Total Exp : Rel Exp : ctc : Exp ctc : Notice : current location : Ready to work from office : any offers : ready for inperson Interview :

Job Title - S&C Global Network - AI - Retail - Consultant - Retail Specialized Data Scientist/ Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary : The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. Stay updated on the latest trends in data science and retail technology. Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills : Strong analytical and statistical skills. Expertise in machine learning and AI. Experience with retail-specific datasets and KPIs. Proficiency in data visualization and reporting tools. Ability to work with large datasets and complex data structures. Strong communication skills to interact with both technical and non-technical stakeholders. A solid understanding of the retail business and consumer behavior. Programming Languages:Python, R, SQL, Scala Data Analysis Tools:Pandas, NumPy, Scikit-learn, TensorFlow, Keras Visualization Tools:Tableau, Power BI, Matplotlib, Seaborn Big Data Technologies:Hadoop, Spark, AWS, Google Cloud Databases:SQL, NoSQL (MongoDB, Cassandra) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Principal AI Data Scientist full-time remote from anywhere in the India #LI-Remote Description: The Principal, AI Data Scientist will be responsible for supporting the implementation of innovative, complex and transformative AI/ML/GenAI solutions across the areas of Clinical Trial Execution and Digital Healthcare across Research and Development. Essential Functions: Support the development and implementation of AI/ML/GenAI solutions to optimize clinical trial operations, including such areas as patient recruitment, patient retention, real-time data monitoring and automated data collection system build. Support the development and implementation GenAI applications for automated clinical trial documentation generation including such areas medical reports, clinical study reports, protocols and patient narratives. Support the development and implementation of Digital Healthcare applications for medical and scientific tools, RWE new ways of generating real data, patients engagement. Support the design and develop predictive models and generative AI solutions using diverse healthcare data sources, including clinical trials data, electronic health records, wearable devices, patient-reported outcomes, HEOR data, phase IV studies. Ensuring compliance with regulatory requirements and data privacy standards. Required Knowledge, Skills and Abilities: Strong programming skills in Python, R, or similar languages, with experience in modern ML frameworks (PyTorch, TensorFlow). Demonstrated experience with generative AI technologies, including LLM architectures and frameworks. Knowledge/experience with digital healthcare tools design and development Experience with natural language processing and generative AI for medical text analysis, generation, and interpretation. Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity with high compute cloud-based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Minimum Requirements Advanced degree (MS or PhD) in Data Science, Computer Science, Biostatistics, or related field 3 - 5 years of related professional experience, with 1+ years of experience applying AI/ML techniques to healthcare or clinical research data. Experience in healthcare/AI implementation in healthcare field is a plus. Knowledge of digital healthcare tools design and development

Job Title: R Shiny Engineer/Data Scientist Required Experience: 3-4 years Job Description: As the Data Scientist, you will play a pivotal role in driving data-driven decision-making and advancing our organization's AI and analytical capabilities. You will lead a team of data scientists, collaborate with cross-functional teams, and contribute to the development and implementation of AI and advanced analytics solutions. This position requires a strong combination of technical expertise, leadership skills, and business acumen . Responsibilities: Team Leadership: Lead, mentor, and inspire a team of junior data scientists, fostering a collaborative and innovative work environment. Provide technical guidance, set priorities, and ensure the team's alignment with organizational goals. Conduct regular performance assessments and contribute to professional development plans. Strategy and Planning: Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data to achieve strategic goals. Develop and execute a data science roadmap, ensuring alignment with overall business and technology strategies. Stay abreast of industry trends, emerging technologies, and best practices in data science. Advanced Analytics and Statistical Modeling: Design, develop, and implement advanced machine learning models and statistical algorithms to extract insights and solve complex business problems. Apply robust statistical process control (SPC), univariate and multivariate analysis, and both parametric and non-parametric statistical techniques. Conduct hypothesis testing, PCA, Shapiro-Wilk test, Anderson-Darling test, Box-Cox transformation, and other statistical methods to ensure data quality and model validity. Work extensively with batch genealogy data and large manufacturing datasets to uncover patterns and optimize operational efficiency. Ensure strong statistical analysis support for both normal and non-normal distributions R Shiny Application Development: Develop and maintain robust, interactive R Shiny applications to support dynamic data exploration and decision-making platforms. Build scalable and user-driven front-end interfaces for real-time statistical analysis and visualization. Collaborate with backend engineers to integrate R Shiny platforms with Redshift and other data sources for seamless analytics delivery. Cross-functional Collaboration: Collaborate with cross-functional teams, including business analysts, software engineers, and domain experts, to integrate data science solutions into business processes. Communicate complex analytical findings to non-technical stakeholders in a clear and actionable manner. Data Governance and Quality: Establish and enforce data governance standards to ensure the accuracy, reliability, and security of data used for analysis. Work with data engineering teams to enhance data quality and integrity throughout the data lifecycle. Project Management: Oversee the end-to-end execution of data science projects, ensuring timelines, budgets, and deliverables are met. Provide regular project updates to stakeholders and manage expectations effectively. Technical Expertise: Provide technical guidance and execution for the latest GenAI technologies, including but not limited to LLM/SLM/VLM and Multi-modal AI Algorithms. Leverage Transformers for complex natural language processing-based tasks. Lead the development of deep learning technologies like computer vision for image processing, OCR/IDP, object detection and tracking, segmentation, Image generation, Convolutional Neural Networks, Capsule Networks, etc Development of core Machine Learning algorithms like time series analysis with Neural ODEs; Variational Autoencoders for Image Generation and anomaly detection; Provide oversight for core deep learning algorithms like Neural Architecture Search for optimization and Graph Neural Networks for molecular structures. Qualifications: Master's or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, etc.) Minimum 1.5+ years of experience leading a team of junior data scientists, with a proven track record of successful project implementations. Proven experience in developing and deploying R Shiny applications for real-time analytics and statistical platforms. In-depth experience with SPC, hypothesis testing, PCA, Shapiro-Wilk test, Anderson-Darling test, Box-Cox transformation, and batch genealogy analysis. Experience in developing statistical solutions for both normal and non-normal distributions, and applying both univariate and multivariate techniques. Experience with GenAI, Agentic AI, LLM Training, and LLM-driven workflow development. Knowledge of large multi-modal models is a must. Experience in MLOps, Statistical Modeling, and Data Visualization. Must have experience with the development and implementation of various core Machine Learning algorithms mentioned above. Must have hands-on experience with Deep Learning technologies for computer vision and image processing, as well as core neural network applications like optimization. Experience in developing ML, AI, and Data Science solutions and putting solutions in production, with proficiency in Data Engineering, is desirable. Experience in the development and implementation of scalable and efficient data pipelines using AWS services such as SageMaker, S3, Glue, and/or Redshift. Excellent leadership, communication, and interpersonal skills. Experience with big data technologies and cloud platforms is a plus. Industry IT Services and IT Consulting

Job Title: Sr. Data Scientist Location: Office-Based (Ahmedabad, India) About Hitech Hitech is a leading provider of Data, Engineering Services, and Business Process Solutions. With robust delivery centers in India and global sales offices in the USA, UK, and the Netherlands, we enable digital transformation for clients across industries including Manufacturing, Real Estate, and e-Commerce. Our Data Solutions practice integrates automation, digitalization, and outsourcing to deliver measurable business outcomes. As we continue expanding, were looking for a skilled Lead Data Scientist to guide innovation, lead teams, and solve complex problems using advanced analytics and machine learning. Position Summary As a Lead Data Scientist, you will lead a team of data scientists, machine learning engineers, and big data specialists to design, develop, and deploy data-driven solutions. You will be responsible for identifying business opportunities, translating them into data strategies, and driving measurable outcomes. This role demands strong leadership, deep technical expertise, and a passion for continuous innovation. Key Responsibilities Manage a team of data scientists, machine learning engineers, and big data specialists. Lead data mining, data collection, and cleansing procedures. Ensure high standards of data quality and integrity across all projects. Interpret complex data sets to identify patterns, trends, and actionable insights. Conceive, plan, and prioritize data science initiatives aligned with business goals. Develop and deploy scalable analytics systems and predictive models. Test and validate data-driven products for performance and reliability. Create compelling visualizations and comprehensive reports for stakeholders. Experiment with emerging models and machine learning techniques for innovation. Qualifications & Experience 6-8 years of working experience in Image Processing using deep learning frameworks such as OpenCV, PyTorch, TensorFlow, Theano, and Caffe. Experience in Text Analytics using NLP tools and techniques on unstructured data. Proven track record in building, deploying, and scaling statistical and deep learning models. Experience with large-scale data (structured and unstructured), data management, parallel computing, and distributed systems. Ability to thrive with minimal supervision in a dynamic, fast-paced environment. Capability to understand diverse business processes and quickly contextualize data requirements. Strong problem-solving skills to translate business problems into actionable data strategies. Excellent communication skills (verbal and written) with a learning and innovation mindset. Strong passion for leveraging AI/ML to solve business problems and a proactive approach to experimentation. Hands-on experience with exploratory data analysis, machine learning, and advanced analytics methods. What We Offer Competitive compensation based on skills and experience. Leadership role in building and scaling AI/ML initiatives. Opportunity to work on high-impact global projects with cutting-edge technologies. Continuous learning, innovation, and professional development support. A collaborative, inclusive, and tech-driven workplace environment. If you're passionate about driving innovation through data and leading a dynamic team to solve real-world problems, wed love to hear from you. Anand Soni Hitech Digital Solutions

company name=Apptad Technologies Pvt Ltd., industry=Employment Firms/Recruitment Services Firms, experience=7 to 13 , jd= Data Scientist Python and Notebooks Responsibilities We are seeking a talented Data Scientist to join our team and drive datadriven decisionmaking across our organization The ideal candidate will have a strong background in statistical analysis machine learning and data visualization with experience working with large datasets in a Teradata environment Responsibilities Design and implement endtoend data science projects from problem definition to model deployment Develop and apply advanced machine learning algorithms and statistical models to solve complex business problems Collaborate with crossfunctional teams to identify opportunities for datadriven improvements Conduct exploratory data analysis and feature engineering to prepare data for modeling Create and maintain dashboards and reports to communicate insights to stakeholders Optimize data collection procedures and ensure data quality Stay current with the latest advancements in data science and machine learning techniques Implement and maintain onpremise AIML solutions Apply Explainable AI techniques to enhance model interpretability and transparency 1013 years of experience in data science or related field Strong proficiency in Python R and SQL Experience with Teradata and data lakelakehouse architectures Expertise in machine learning algorithms statistical modeling and data visualization Familiarity with big data technologies eg Hadoop Spark Excellent problemsolving and communication skills Experience with version control systems eg Git Experience with onpremise AIML solutions Knowledge of Explainable AI methods and their practical applications , Title=Data Scientist, ref=6566343

Design, implement, and evaluate data-driven solutions using advanced machine learning and Agentic AI frameworks. Work on LLM-based architectures, including prompt engineering, memory systems, and agent orchestration (e.g., LangChain, AutoGPT).

Job Title: Data Scientist Location: Mumbai/Indore/Surat Job Type: Full-time About Us: Everestek is a forward-thinking organization specializing in designing and deploying cutting-edge AI solutions. From powerful recommendation engines and intuitive chatbots to state-of-the-art generative AI and deep learning applications, we empower businesses to harness the full potential of their data. Our mission is to create transformative, data-driven products that enable our clients to innovate faster, personalize their offerings, and stay ahead in an ever-evolving tech landscape. At Everestek, we foster a culture of collaboration, creativity, and continuous learning. Our dynamic team of data scientists, engineers, and innovators is dedicated to pushing the boundaries of what's possible in artificial intelligence. If youre passionate about solving complex problems and want to be part of an organization that values experimentation and impact, Everestek is the place for you. Key Responsibilities: Design, build, and optimize machine/deep learning models, including predictive models, recommendation systems, and Gen-AI-based solutions. Develop and implement advanced AI agents capable of performing autonomous tasks, decision-making, and executing requirement-specific workflows. Prompt engineer to develop new and enhance existing Gen-AI applications. (Chatbots, RAG) Perform advanced data manipulation, cleansing, and analysis to extract actionable insights from structured and unstructured data. Create scalable and efficient recommendation systems that enhance user personalization and engagement. Design and deploy AI-driven chatbots and virtual assistants, focusing on natural language understanding and contextual relevance. Implement and optimize machine and deep learning models for NLP tasks, including text classification, sentiment analysis, and language generation. Explore, develop, and deploy state-of-the-art technologies for AI agents, integrating them with broader enterprise systems. Collaborate with cross-functional teams to gather business requirements and deliver AI-driven solutions tailored to specific use cases. Automate workflows using advanced AI tools and frameworks to increase efficiency and reduce manual interventions. Stay informed about cutting-edge advancements in AI, machine learning, NLP, and Gen AI applications, and assess their relevance to the organization. Effectively communicate technical solutions and findings to both technical and non-technical stakeholders. Qualifications and Skills: Required: At least 3 years of experience working with data sciences. Python proficiency and hands-on experience with libraries like (Pandas, Numpy, Matplotlib, NLTK, Sklearn, and Tensorflow) Proven experience in designing and implementing AI agents and autonomous systems. Strong expertise in machine learning, including predictive modeling and recommendation systems. Hands-on experience with deep learning frameworks like TensorFlow or PyTorch, focusing on NLP and AI-driven solutions. Advanced understanding of natural language processing (NLP) techniques and tools, including transformers like BERT, GPT, or similar models including open-source LLMs. Experience in prompt engineering for AI models to enhance functionality and adaptability. Strong knowledge of cloud platforms (AWS) for deploying and scaling AI models. Familiarity with AI agent frameworks like LangChain, OpenAI APIs, or other agent-building tools. Advanced skills in Relational databases [Postgres], Vector Database, querying, analytics, semantic search, and data manipulation. Strong problem-solving and critical-thinking skills, with the ability to handle complex technical challenges. Hands-on experience working with API frameworks like Flask, FastAPI, etc. Git and GitHub proficiency. Excellent communication & documentation skills to articulate complex ideas to diverse audiences. Preferred: Hands-on experience building and deploying conversational AI, chatbots, and virtual assistants. Familiarity with MLOps pipelines and CI/CD for AI/ML workflows. Experience with reinforcement learning or multi-agent systems. BE (OR Master) in Computer Science, Data Science, or Artificial Intelligence. Agentic AI systems using frameworks like Langchain or similar.

We are looking for a Data Scientist to help us gain useful insight from raw data. Data scientists' responsibilities include working with the data science team, planning projects, and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Responsibilities Responsible for overseeing the data scientists' team and data specialists. Teach, lead, and counsel colleagues on new techniques or solutions. Collaborate with data and software engineers to enable the deployment of sciences and technologies that will scale across the company's ecosystem. Responsible for the conception, planning, and prioritizing of data projects. Responsible for building analytic systems and predictive models, as well as experimenting with new models and techniques. Ensure that data projects align with organizational goals. Requirements Master's degree in Computer Science, Operations Research, Econometrics, Statistics, or related technical field. 3+ years of experience solving analytical problems using quantitative approaches. Experience communicating quantitative analysis results. Knowledge of relational databases and SQL. Development experience in any scripting language (PHP, Python, Perl, etc. ). Knowledge of statistics (e. g., hypothesis testing, regression). Experience manipulating data sets through statistical software (ex., R, SAS) or other methods. Must Have Programming - Python (Preferred) / R. ML Models - i. Regression - Linear, Logistic, Multinomial, Mixed effect. Classification - Bagging and Boosting (Random Forest), Decision tree, SVM. Clustering - K-Means, hierarchical, DB-Scan. Time series - ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM, Neural Networks (Deep learning), Naive Bayes, Excel, and SQL. Dimensionality Reduction - PCA, SVD, etc. Optimization Techniques - Linear programming, Gradient Descent, Genetic Algorithm. Cloud - Understanding of Azure / AWS offerings, setting up an ML pipeline in the cloud. Good To Have Visualization - Tableau / Power BI / Looker / QlikView. Data management - HDFS, Spark, Advanced Excel. Agile Tools - Azure DevOps, JIRA, Pyspark, Big Data/Hive Database. IDE: PyCharm. This job was posted by Debapti Roy from mPokket.

Is responsible for building end-to-end machine learning solutions using Python and statistical algorithms on GCP, with a focus on commerce/CPG domains and deployment management .plz share your profile to sheetal.gighub@gmail.com

Experience Required: 2-5Years No. of vacancies: 4 Job Type: Full Time Vacancy Role: WFO Job Category: Development Job Description We are seeking a Data Scientist with strong expertise in data analysis, machine learning, and visualization. The ideal candidate should be proficient in Python, Pandas, and Matplotlib, with experience in building and optimizing data-driven models. Some experience in Natural Language Processing (NLP) and Named Entity Recognition (NER) models would be a plus. Roles & Responsibilities Analyze and process large datasets using Python and Pandas. Develop and optimize machine learning models for predictive analytics. Create data visualizations using Matplotlib and Seaborn to support decision-making. Perform data cleaning, feature engineering, and statistical analysis. Work with structured and unstructured data to extract meaningful insights. Implement and fine-tune NER models for specific use cases (if required). Collaborate with cross-functional teams to drive data-driven solutions. Qualifications 2+ years of professional experience Strong proficiency in Python and data science libraries (Pandas, NumPy, Scikit-learn, etc.). Experience in data analysis, statistical modeling, and machine learning. Hands-on expertise in data visualization using Matplotlib and Seaborn. Understanding of SQL and database querying. Familiarity with NLP techniques and NER models is a plus. Strong problem-solving and analytical skill Job Type: Full-time Pay: ₹900,000.00 - ₹2,000,000.00 per year Benefits: Flexible schedule Leave encashment Provident Fund Schedule: Day shift Work Location: In person

Job Title: Data Scientist Location: Pune (Work From Office) Experience Level: 3–5 Years Positions Available: 5 Job Description: We are seeking a highly motivated and analytically strong Data Scientist to join our team. The ideal candidate should have experience in building and deploying machine learning models, working with large-scale data processing tools, and delivering actionable insights in real-time systems. Key Responsibilities: Develop, train, and deploy ML models using Python , Scikit-Learn , TensorFlow , and PyTorch Perform real-time inference , anomaly detection , and unsupervised learning techniques on high-volume data Build and manage data pipelines using Spark , Airflow , and messaging systems like Kafka Work with modern data architectures including ClickHouse , SQL , PostgreSQL , and analytical databases Implement and optimize risk engines , credit scoring models , and payment system analytics Collaborate with cross-functional teams to integrate data science solutions into production Skills Required: Languages & Libraries: Python, Pandas, Scikit-Learn, TensorFlow, PyTorch Techniques: Real-Time Inference, Anomaly Detection, Unsupervised Learning Tools & Frameworks: Spark, Airflow, Kafka Databases: ClickHouse, SQL, PostgreSQL, Analytical Databases Domain Knowledge: Risk Engines, Credit Scoring, Payments Job Types: Full-time, Permanent Pay: ₹483,299.97 - ₹1,000,000.00 per year Benefits: Provident Fund Schedule: Day shift Monday to Friday Application Question(s): How soon you can join? What is your current CTC & expected CTC? Experience: Scikit-Learn: 5 years (Preferred) TensorFlow: 5 years (Preferred) Pandas: 5 years (Preferred) Kafka: 5 years (Preferred) Work Location: In person

About DeepTek DeepTek is a pioneering healthcare AI company aiming to transform radiology by empowering radiologists with an AI-powered, feature-rich radiology platform and specialized AI models. We leverage cutting-edge technologies to deliver advanced solutions in medical imaging. With a team of over 200+ members, including top-tier application developers, data scientists, and expert radiologists, DeepTek fosters an environment of innovation and collaboration. Job Description We are looking for a Data Scientist who is passionate about working in the healthcare AI domain. This role will involve collaborating with cross-functional teams, including senior data scientists, application developers, and radiology experts, to develop and refine AI solutions for medical imaging. You will gain hands-on experience working on advanced projects and research opportunities in Computer Vision and Deep Learning. Key Responsibilities Develop and optimize deep learning models for medical image analysis, including segmentation, classification, and object detection. Preprocess and clean medical imaging datasets to enhance AI model performance and reliability. Conduct model evaluation, error analysis, and performance benchmarking to improve accuracy and generalization. Collaborate with radiologists and domain experts to refine AI model outputs and ensure clinical relevance. Experience 2-3 years Data Science/Machine Learning experience Required Skills Strong fundamental knowledge of machine learning, computer vision and image processing Demonstrable experience training convolutional neural networks for segmentation and object detection Strong programming skills in Python and familiarity with data science and image processing libraries (e.g., NumPy, pandas, scikit-learn, opencv, PIL). Hands-on experience with deep learning frameworks like Keras or PyTorch. Experience with model evaluation and error analysis. Desired Skills Familiarity with healthcare or radiology datasets. Familiarity with ONNX format Qualification Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field. Company Location Baner, Pune, India https://goo.gl/maps/Fmd22UNSiXYQD2ba9 Please send your resumes at hr@deeptek.ai

Organization: At CommBank, we never lose sight of the role we play in other people’s financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things. Job Title: Data Scientist Location: Bangalore Business & Team: BB Advanced Analytics and Artificial Intelligence COE Impact & contribution: As a Senior Data Scientist, you will be instrumental in pioneering Gen AI and multi-agentic systems at scale within CommBank. You will architect, build, and operationalize advanced generative AI solutions—leveraging large language models (LLMs), collaborative agentic frameworks, and state-of-the-art toolchains. You will drive innovation, helping set the organizational strategy for advanced AI, multi-agent collaboration, and responsible next-gen model deployment. Roles & Responsibilities: Gen AI Solution Development: Lead end-to-end development, fine-tuning, and evaluation of state-of-the-art LLMs and multi-modal generative models (e.g., transformers, GANs, VAEs, Diffusion Models) tailored for financial domains. Multi-Agentic System Engineering: Architect, implement, and optimize multi-agent systems, enabling swarms of AI agents (utilizing frameworks like Lang chain, Lang graph, and MCP) to dynamically collaborate, chain, reason, critique, and autonomously execute tasks. LLM-Backed Application Design: Develop robust, scalable GenAI-powered APIs and agent workflows using Fast API, Semantic Kernel, and orchestration tools. Integrate observability and evaluation using Lang fuse for tracing, analytics, and prompt/response feedback loops. Guardrails & Responsible AI: Employ frameworks like Guardrails AI to enforce robust safety, compliance, and reliability in LLM deployments. Establish programmatic checks for prompt injections, hallucinations, and output boundaries. Enterprise-Grade Deployment: Productionize and manage at-scale Gen AI and agent systems with cloud infrastructure (GCP/AWS/Azure), utilizing model optimization (quantization, pruning, knowledge distillation) for latency/throughput trade offs. Toolchain Innovation: Leverage and contribute to open source projects in the Gen AI ecosystem (e.g., Lang Chain, Lang Graph, Semantic Kernel, Lang fuse, Hugging face, Fast API). Continuously experiment with emerging frameworks and research. Stakeholder Collaboration: Partner with product, engineering, and business teams to define high-impact use cases for Gen AI and agentic automation; communicate actionable technical strategies and drive proof-of-value experiments into production. Mentorship & Thought Leadership: Guide junior team members in best practices for Gen AI, prompt engineering, agentic orchestration, responsible deployment, and continuous learning. Represent CommBank in the broader AI community through papers, patents, talks, and open-source. Essential Skills: 6+ years of hands-on experience in Machine Learning, Deep Learning, or Generative AI domains, including practical expertise with LLMs, multi-agent frameworks, and prompt engineering. Proficient in building and scaling multi-agent AI systems using Lang Chain, Lang Graph, Semantic Kernel, MCP, or similar agentic orchestration tools. Advanced experience developing and deploying Gen AI APIs using Fast API; operational familiarity with Lang fuse for LLM evaluation, tracing, and error analytics. Demonstrated ability to apply Guardrails to enforce model safety, explainability, and compliance in production environments. Experience with transformer architectures (BERT/GPT, etc.), fine-tuning LLMs, and model optimization (distillation/quantization/pruning). Strong software engineering background (Python), with experience in enterprise-grade codebases and cloud-native AI deployments. Experience integrating open and commercial LLM APIs and building retrieval-augmented generation (RAG) pipelines. Exposure to agent-based reinforcement learning, agent simulation, and swarm-based collaborative AI. Familiarity with robust experimentation using tools like Lang Smith, GitHub Copilot, and experiment tracking systems. Proven track record of driving Gen AI innovation and adoption in cross-functional teams. Papers, patents, or open-source contributions to the Gen AI/LLM/Agentic AI ecosystem. Experience with financial services or regulated industries for secure and responsible deployment of AI. Education Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696. Advertising End Date: 01/07/2025

Role & responsibilities Proficient in Excel, SQL, Python/R, and data visualization tools (Power BI, Tableau). Familiarity with SAP modules, KM dashboards, and IoT data sources. Knowledge of predictive modeling, statistical analysis, and machine learning techniques. Exposure to Industry 4.0 concepts, including CBMS and digital twins. Hands-on experience with scripting and automation of reports. Provide training and support to users on data interpretation, dashboard usage, and analytics tools. Preferred candidate profile Prefer candidates from manufacturing background or doing any project for manufacturing industry i.e Pharma, FMCG, cosmetic, chemical, etc. Candidate must have done B.tech in chemical, Instrumentation, Mechatronics field .

We are growing our world-class team of mission-driven, entrepreneurial Data Scientists who are passionate about broadening financial inclusion by untapping insights from non-traditional data. Be part of the team responsible for developing and enhancing Oportun's core intellectual property used in scoring risk for underbanked consumers that lack a traditional credit bureau score. In this role you will be on the cutting edge working with large and diverse (i.e. data from dozens of sources including transactional, mobile, utility, and other financial services) alternative data sets and utilize machine learning and statistical modeling to build scores and strategies for managing risk, collection/loss mitigation, and fraud. You will also drive growth and optimize marketing spend across channels by leveraging alternative data to help predict which consumers would likely be interested in Oportuns affordable, credit building loan product. RESPONSIBILITIES Develop data products and machine learning models used in Risk, Fraud, Collections, and portfolio management, and provide frictionless customer experience for various products and services Oportun provides. Build accurate and automated monitoring tools which can help us to keep a close eye on the performance of the models and rules. Build model deployment platform which can shorten the time of implementing new models. Build end-to-end reusable pipelines from data acquisition to model output delivery. Lead initiatives to drive business value from start to finish including project planning, communication, and stakeholder management. Lead discussions with Compliance, Bank Partners, and Model Risk Management teams to facilitate the Model Governance Activities such as Model Validations and Monitoring REQUIREMENTS A relentless problem solver and out of the box thinker with a proven track record of driving business results in a timely manner Masters degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline (Bachelor’s degree with significant relevant experience will be considered). Hands on experience leveraging machine learning techniques such as Gradient Boosting, Logistic Regression and Neural Network to solve real world problems 3+ years of hands-on experience with data extraction, cleaning, analysis and building reusable data pipelines; Proficient in SQL, Spark SQL and/or Hive 3+ years of experience in leveraging modern machine learning toolset and programming languages such as Python Excellent written and oral communication skills Strong stakeholder management and project management skills Comfortable in a high-growth, fast-paced, agile environment Experience working with AWS EMR, Sage-maker or other cloud-based platforms is a plus Experience with HDFS, Hive, Shell script and other big data tools is a plus

Key Responsibilities Lead research initiatives to improve OCR accuracy across diverse document types and languages Train and fine-tune LLMs using domain-specific data to enhance performance in specialized contexts Develop techniques to scale LLMs efficiently for high-volume production environments Design and implement novel approaches to model optimization and evaluation Collaborate with cross-functional teams to integrate AI solutions into production systems Stay current with the latest research and incorporate state-of-the-art techniques Document methodologies, experiments, and findings for both technical and non-technical audiences Required Qualifications PhD in Computer Science, Machine Learning, AI, or a related field (completed within the last year) Strong understanding of deep learning architectures, particularly transformer-based models Experience with OCR systems and techniques for improving text recognition accuracy Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX) Demonstrated ability to implement and adapt research papers into working code Excellent problem-solving skills with a methodical approach to experimentation Strong communication skills to explain complex technical concepts clearly

We are seeking a highly motivated and analytical Data Scientist to join our team. In this role, you will be responsible for extracting insights from complex datasets to drive business decisions and improve performance. You will work closely with cross-functional teams to develop data models, create visualizations, and apply machine learning techniques to solve real-world problems. Key Responsibilities: Collect, clean, and preprocess structured and unstructured data from various sources. Build predictive models and machine learning algorithms. Analyze large datasets to identify trends, patterns, and opportunities. Communicate findings through visualizations and reports to both technical and non-technical stakeholders. Collaborate with product, engineering, and business teams to define data-driven strategies. Deploy models and monitor performance in production environments. Continuously improve data science processes and methodologies. Requirements: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Proven experience (0 - 4+ years) as a Data Scientist or similar role. Proficiency in programming languages such as Python or R. Strong knowledge of SQL and experience with data querying. Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, XGBoost). Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Excellent analytical and problem-solving skills. Strong communication and collaboration abilities. Contact Person: Rakesh HR Contact Person: 9003745749 Experience: 0 - 4+ Years Location: Coimbatore Timings: 09.30 Am - 06.30 Pm Job Types: Full-time, Permanent Pay: ₹367,715.72 - ₹1,018,606.26 per year Benefits: Health insurance Provident Fund Schedule: Day shift Morning shift Rotational shift Supplemental Pay: Performance bonus Yearly bonus Work Location: In person

Role: Data Scientist Location: India (Remote) About Lingaro: Lingaro Group is the end-to-end data services partner to global brands and enterprises. We lead our clients through their data journey, from strategy through development to operations and adoption, helping them to realize the full value of their data. Since 2008, Lingaro has been recognized by clients and global research and advisory firms for innovation, technology excellence, and the consistent delivery of highest-quality data services. Our commitment to data excellence has created an environment that attracts the brightest global data talent to our team. About DS/AI Competency Center: Focuses on leveraging data, analytics, and artificial intelligence (AI) technologies to extract insights, build predictive models, and develop AI powered solutions. Utilizes Exploratory Data Analysis, Statistical Modeling and Machine Learning, Model Deployment, and Integration as well as Model Monitoring and Maintenance. Delivers business solutions using multiple AI techniques and tools. Website: https://lingarogroup.com/ Requirements: Must Have: 5+ years of relevant professional experience, including 2+ of DS/Operations Research experience. Experience in optimization methodologies, including use of various optimization libraries (e.g. CPLEX, Gurobi, ortools, etc.). Strong Python coding skills (including Object oriented programming concepts), including using ML libraries and basic working knowledge of SQL Experience working in cloud technologies (preferred MS Azure, GCP nice-to-have). Familiarity with theory behind various machine learning concepts Experience in CRISP-DM projects delivery and with Agile project (like Scrum, Kanban). Experience with business requirements gathering, transforming them into technical plan, data processing, feature engineering, models evaluation, hypothesis testing and model deployment. Experience in working with client-facing role. Able to apply independent research, gather information, and give recommendation how to solve problems of diverse scope. Great communication skills. Nice to have: Other programming languages knowledge e.g., SQL, R Experience working in Spark (PySpark) Experience in working in other IT roles (Data Engineer, AI Engineer, Business Intelligence-related) is welcomed Understanding and experience in applying Data Science/Machine Learning methods to Supply Chain (Manufacturing, Transportation, Warehousing, Inventory or Sustainability) Strong statistical/mathematical background Experience in working in matrix organization Tasks: Business understanding, Data understanding/preparation, Modeling, Evaluation and Deployment of solutions – following CRISP-DM methodologies. Understanding of optimization methodologies including linear/integer/nonlinear programming and heuristics for finding the best solution to the business problem. Experience with business requirements gathering, transforming them into technical plan, data processing, feature engineering, hypothesis testing, transforming findings into tasks, Proactive approach for areas where improvement is needed, like suggestions of improving existing pipelines (tests, support, and improvements) Creation and following of standards to improve competency quality. Know-how and experience from projects in Supply Chain area, or optimization projects is a plus Why join us: Stable employment. On the market since 2008, 2000+ talents currently on board in 7+ global sites. 100% remote. Flexibility regarding working hours. Full-time position Comprehensive online onboarding program with a “Buddy” from day 1. Cooperation with top-tier engineers and experts. Unlimited access to the Udemy learning platform from day 1. Certificate training programs. Lingarians earn 500+ technology certificates yearly. Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. Grow as we grow as a company. 76% of our managers are internal promotions. A diverse, inclusive, and values-driven community. Autonomy to choose the way you work. We trust your ideas. Create our community together. Refer your friends to receive bonuses. Activities to support your well-being and health. Plenty of opportunities to donate to charities and support the environment. Please click on this website to submit your application: https://system.erecruiter.pl/FormTemplates/RecruitmentForm.aspx?WebID=58b86d44db3b4c5993eab2801d9d9a01

About the job About us We are surrounded by the world's leading consumer companies led by technology - Amazon for retail, Airbnb for hospitality, Uber for mobility, Netflix and Spotify for entertainment, etc. Food & Beverage is the only consumer sector where large players are still traditional restaurant companies. At Rebel Foods, we are challenging this status quo as we are building the world's most valuable restaurant company on the internet, superfast. The opportunity for us is immense due to the exponential growth in the food delivery business worldwide which has helped us build 'The World's Largest Internet Restaurant Company' in the last few years. Rebel Foods' current presence is India, Indonesia, UAE, UK & KSA with close to 50 brands and 4500+ internet restaurants has been built on The Rebel Operating System . While for us it is still Day 1, we know we are in the middle of a revolution towards creating never seen before customer-first experiences. We bring you a once-in-a-lifetime opportunity to disrupt the 500-year-old industry with technology at its core. Job Description We are looking f or a Data Scienti st-II to join our Data Science & Analytics (DSA) Team. You will get to work with other data scientists, analysts, data engineers, PMs and business teams on some of the toughest and most interesting problems in our industry. Our work spans across areas of inventory forecasting, order predictions, marketing spend optimization, delivery time prediction, personalization, customer insighting, product recommendations, supply chain planning, capacity optimization, and more. The role will involve understanding business problems, designing relevant ML solutions, building & deploying new models, maintaining & enhancing existing models, and automating performance measurement of the same. We are looking for someone who is excited to work in a fast-growing industry, has a spirit of ownership & collaboration, and loves seeing the impact of what they have built at scale! What our team owns at Rebel, the Data Science & Analytics team builds and maintains all ML models, rule-based intelligence, automated reports and dashboards used by the organization. We are on a mission to drive business impact via ML and Data Science and grow adoption of these areas at Rebel. We also want to enable the organization to better understand and effectively use ML and DS. We interact with teams across every business area such as Supply, Operations, Demand Generation, D2C, Finance, Brands, Customer Delight, Central Planning and many more. We are never short of interesting challenges and we balance delivering continuous impact and great CX, while building strong foundations to drive sustainable ML returns overtime. Specific Qualifications Strong working knowledge of a variety of machine learning techniques (Regression, Classification,Clustering, Decision Tree, Probability Networks, Neural Networks, Bayesian models etc.) Proficient in Python, SQL, and machine learning libraries (e.g., TensorFlow,scikit-learn). Experience in working with varied data types (structured and unstructured) and databases Experience with Machine Learning and related technologies such as Python, Tensorflow, Amazon SageMaker Excellent problem-solving skills with a demonstrated ability to think analytically and strategically. Good-to-have Experience solving NLP-based problems or working with LLMs / prompt engineering Working with non-tech stakeholders and explaining ML performance in simple language A love of food (Yes, we have regular tasting sessions at office!) Share across your cv's to v-noor.fazilath@rebelfoods.com

We are looking for a highly skilled and motivated Data Scientist with deep experience in building recommendation systems to join our team. This role demands expertise in deep learning, embedding-based retrieval, and the Google Cloud Platform (GCP). You will play a critical role in developing intelligent systems that enhance user experiences through personalized content discovery. Key Responsibilities: Develop, train, and deploy recommendation models using two-tower, multi-tower, and cross-encoder architectures . Generate and utilize text/image embeddings (e.g., CLIP , BERT , Sentence Transformers ) for content-based recommendations. Design semantic similarity search pipelines using vector databases (FAISS, ScaNN, Qdrant, Matching Engine). Create and manage scalable ML pipelines using Vertex AI , Kubeflow Pipelines , and GKE . Handle large-scale data preparation and feature engineering using Dataproc (PySpark) and Dataflow . Implement cold-start strategies leveraging metadata and multimodal embeddings. Work on user modeling , temporal personalization , and re-ranking strategies . Run A/B tests and interpret results to measure real-world impact. Collaborate with cross-functional teams (Engineering, Product, DevOps) for model deployment and monitoring. Must-Have Skills: Strong command of Python and ML libraries: pandas, polars, numpy, scikit-learn, matplotlib, tensorflow, torch, transformers. Deep understanding of modern recommender systems and embedding-based retrieval . Experience with TensorFlow , Keras , or PyTorch for building deep learning models. Hands-on with semantic search , ANN search , and real-time vector matching . Proven experience with Vertex AI , Kubeflow on GKE , and ML pipeline orchestration. Familiarity with vector DBs such as Qdrant , FAISS , ScaNN , or Matching Engine on GCP. Experience in deploying models via Vertex AI Online Prediction , TF Serving , or Cloud Run . Knowledge of feature stores , embedding versioning , and MLOps practices (CI/CD, monitoring). Preferred / Good to Have: Experience with ranking models (e.g., XGBoost , LightGBM , DLRM ) for candidate scoring. Exposure to LLM-powered personalization or hybrid retrieval systems. Familiarity with streaming pipelines using Pub/Sub , Dataflow , Cloud Functions . Hands-on with multi-modal retrieval (text + image + tabular data). Strong grasp of cold-start problem solving , using enriched metadata and embeddings. GCP Stack You’ll Work With: ML & Pipelines: Vertex AI, Vertex Pipelines, Kubeflow on GKE Embedding & Retrieval: Matching Engine, Qdrant, FAISS, ScaNN, Milvus Processing: Dataproc (PySpark), Dataflow Ingestion & Serving: Pub/Sub, Cloud Functions, Cloud Run, TF Serving CI/CD & Automation: GitHub Actions, GitLab CI, Terraform

Job Title: Senior Data Scientist Location: Bangalore (Hybrid) Experience: 3+ Years Job Type: Full-Time About the Role We’re looking for a Senior Data Scientist to help us uncover insights from large datasets and power smarter decisions. You’ll apply forecasting, machine learning, and data visualization techniques to solve complex business problems and improve product performance. Key Responsibilities Apply statistical forecasting algorithms to predict short and long-term business outcomes Build predictive models and machine learning solutions for real-world applications Leverage deep learning to enhance forecast accuracy (preferred) Translate business challenges into structured analytical problems Present insights through data storytelling and visualization using tools like Tableau Collaborate with cross-functional teams to integrate models into products Mandatory Skills 3+ years hands-on experience as a Data Scientist Strong proficiency in SQL and Python Experience with machine learning , predictive analytics , and forecasting techniques Knowledge of deep learning frameworks (Keras, TensorFlow, etc.) is a plus Proficiency in Tableau or similar BI tools Excellent communication and presentation skills

Job Description - AI Data Scientist Location: Remote Department: Data & AI Engineering Employment Type: Full-time Experience Level: Mid-level About the Role: We are seeking an experienced AI Data Engineer to design, build, and deploy data pipelines and ML infrastructure to power scalable AI/ML solutions. This role involves working at the intersection of data engineering, MLOps, and model deployment—supporting the end-to-end lifecycle from data ingestion to model production. Key Responsibilities: Data Engineering & Development Design, develop, and train AI models to solve complex business problems and enable intelligent automation. Design, develop, and maintain scalable data pipelines and workflows for AI/ML applications. Ingest, clean, and transform large volumes of structured and unstructured data from diverse sources (APIs, streaming, databases, flat files). Build and manage data lakes, data warehouses, and feature stores. Prepare training datasets and implement data preprocessing logic. Perform data quality checks, validation, lineage tracking, and schema versioning. Model Deployment & MLOps Package and deploy AI/ML models to production using CI/CD workflows. Implement model inference pipelines (batch or real-time) using containerized environments (Docker, Kubernetes). Use MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) for model tracking, versioning, and deployment. Monitor deployed models for performance, drift, and reliability. Integrate deployed models into applications and APIs (e.g., REST endpoints). Platform & Cloud Engineering Manage cloud-based infrastructure (AWS, GCP, or Azure) for data storage, compute, and ML services. Automate infrastructure provisioning using tools like Terraform or CloudFormation. Optimize pipeline performance and resource utilization for cost-effectiveness. Requirements: Must-Have Skills Bachelor's/Master’s in Computer Science, Engineering, or related field. 2+ years of experience in data engineering, ML engineering, or backend infrastructure. Proficient in Python, SQL, and data processing frameworks (e.g., Spark, Pandas). Experience with cloud platforms (AWS/GCP/Azure) and services like S3, BigQuery, Lambda, or Databricks. Hands-on experience with CI/CD, Docker, and container orchestration (Kubernetes, ECS, EKS). Preferred Skills Experience deploying ML models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Familiarity with API development (Flask/FastAPI) for serving models. Experience with Airflow, Prefect, or Dagster for orchestrating pipelines. Understanding of DevOps and MLOps best practices. Soft Skills: Strong communication and collaboration with cross-functional teams. Proactive problem-solving attitude and ownership mindset. Ability to document and communicate technical concepts clearly.

Job Title: Data Scientist Location: Pune (Work From Office) Experience Level: 3–5 Years Positions Available: 5 Job Description: We are seeking a highly motivated and analytically strong Data Scientist to join our team. The ideal candidate should have experience in building and deploying machine learning models, working with large-scale data processing tools, and delivering actionable insights in real-time systems. Key Responsibilities: Develop, train, and deploy ML models using Python , Scikit-Learn , TensorFlow , and PyTorch Perform real-time inference , anomaly detection , and unsupervised learning techniques on high-volume data Build and manage data pipelines using Spark , Airflow , and messaging systems like Kafka Work with modern data architectures including ClickHouse , SQL , PostgreSQL , and analytical databases Implement and optimize risk engines , credit scoring models , and payment system analytics Collaborate with cross-functional teams to integrate data science solutions into production Skills Required: Languages & Libraries: Python, Pandas, Scikit-Learn, TensorFlow, PyTorch Techniques: Real-Time Inference, Anomaly Detection, Unsupervised Learning Tools & Frameworks: Spark, Airflow, Kafka Databases: ClickHouse, SQL, PostgreSQL, Analytical Databases Domain Knowledge: Risk Engines, Credit Scoring, Payments Job Types: Full-time, Permanent Pay: ₹483,299.97 - ₹1,000,000.00 per year Benefits: Provident Fund Schedule: Day shift Monday to Friday Application Question(s): How soon you can join? What is your current CTC & expected CTC? Experience: Scikit-Learn: 5 years (Preferred) TensorFlow: 5 years (Preferred) Pandas: 5 years (Preferred) Kafka: 5 years (Preferred) Work Location: In person

Key Responsibilities Lead research initiatives to improve OCR accuracy across diverse document types and languages Train and fine-tune LLMs using domain-specific data to enhance performance in specialized contexts Develop techniques to scale LLMs efficiently for high-volume production environments Design and implement novel approaches to model optimization and evaluation Collaborate with cross-functional teams to integrate AI solutions into production systems Stay current with the latest research and incorporate state-of-the-art techniques Document methodologies, experiments, and findings for both technical and non-technical audiences Required Qualifications PhD in Computer Science, Machine Learning, AI, or a related field (completed within the last year) Strong understanding of deep learning architectures, particularly transformer-based models Experience with OCR systems and techniques for improving text recognition accuracy Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX) Demonstrated ability to implement and adapt research papers into working code Excellent problem-solving skills with a methodical approach to experimentation Strong communication skills to explain complex technical concepts clearly