2233 Data Scientist Jobs - Page 23

Data Scientist III Data Science 1 About Junglee Games: With over 140 million users, Junglee Games is a leader in the online skill gaming space. Founded in San Francisco in 2012 and part of the Flutter Entertainment Group, we are revolutionizing how people play games. Our notable games include Howzat, Junglee Rummy, and Junglee Poker. Our team comprises over 1000 talented individuals who have worked on internationally acclaimed AAA titles like Transformers and Star Wars: The Old Republic and contributed to Hollywood hits such as Avatar. Junglee s mission is to build entertainment for millions of people around the world and connect them through games. Junglee Games is not just a gaming company but a blend of innovation, data science, cutting-edge tech, and, most importantly, a values-driven culture that is creating the next set of conscious leaders. Job overview: As our Data Scientist III, you will be a key driver of strategic and tactical data science projects. You ll partner closely with Product, Marketing, and Engineering teams to influence decisions and optimize outcomes using data, models, and experimentation. Job Location: Gurgaon Key Responsibilities: Lead complex analytics projects end-to-end: problem scoping, data wrangling, modeling, validation, and communication. Develop and deploy statistical models and machine learning solutions to improve core metrics (e. g. , retention, monetization, user segmentation, etc. ). Own experimentation and causal inference for product features (A/B testing, uplift modeling, etc. ). Translate business problems into quantitative solutions and drive product and marketing roadmap with data insights. Collaborate with Data Engineering to design scalable data pipelines and ML deployment workflows. Qualifications & skills required: 5 7 years of experience in data science, preferably in B2C, gaming, consumer tech, or related industries. Strong foundation in statistics, probability, and machine learning (classification, regression, clustering, time-series, etc. ). Hands-on experience with Python/R and SQL. Experience with tools like Airflow, Spark, DBT, or similar is a plus. Experience designing and analyzing experiments (A/B testing, DoE). Strong problem-solving mindset with a focus on impact and ownership. Excellent communication skills; ability to simplify complex findings for non-technical stakeholders. Be a part of Junglee Games to: Value Customers & Data - Prioritize customers, use data-driven decisions, master KPIs, and leverage ideation and A/B testing to drive impactful outcomes. Inspire Extreme Ownership - We embrace ownership, collaborate effectively, and take pride in every detail to ensure every game becomes a smashing success. Lead with Love - We reject micromanagement and fear, fostering open dialogue, mutual growth, and a fearless yet responsible work ethic. Embrace change - Change drives progress and our strength lies in adapting swiftly and recognizing when to evolve to stay ahead. Play the Big Game - We think big, challenge norms, and innovate boldly, driving impactful results through fresh ideas and inventive problem-solving. Avail a comprehensive benefits package that includes paid gift coupons, fitness plans, gadget allowances, fuel costs, family healthcare, and much more. Know more about us Explore the world of Junglee Games through our website, www. jungleegames. com . Get a glimpse of what Life at Junglee Games looks like on LinkedIn . Here is a quick snippet of the Junglee Games Offsite 24 Liked what you saw so far Be A Junglee

Area(s) of responsibility Key Responsibilities Design, develop, extend and maintain end-to-end data workflows and pipelines in Dataiku DSS. Collaborate with data scientists and analysts to operationalize machine learning models. Leverage Generative AI models and tools within Dataiku to build advanced AI-powered applications and analytics solutions. Integrate Dataiku with various data sources (databases, cloud storage, APIs). Develop and optimize SQL queries and Python/R scripts for data extraction and transformation across relational and NoSQL databases Work extensively with cloud data warehouses like Amazon Redshift and/or Snowflake for data ingestion, transformation, and analytics. Implement automation and scheduling of data workflows. Monitor and troubleshoot data pipelines to ensure data quality and reliability. Document technical solutions and best practices for data processing and analytics.

Job description We are having a F2F weekend drive for the requirement of a Data Scientist + Gen AI at our LTIM Hyderabad office. Date - 5th July 2025 Experience - 6+ Years Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS, AI/ML, NLP Location - LTIMindtree Hyderabad Office Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment Generic JD- More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.

- Extract, clean, and model large datasets (SQL + Python) and translate findings into clear narratives for VP/C-level reviews. - Design and maintain Tableau/Power BI dashboards used by 100+ internal users. - A/B Testing Required Candidate profile Bachelor’s degree (Master’s preferred). Relevant experience Proficiency in Python, and SQL. Solid knowledge of machine learning algorithms, statistics, and predictive modeling.

3+ years of Data science exp understanding of machine learning. understanding of SQL & Python.Power BI or Tableau Industry specific (CPG, Manufacturing) use cases is required fine-tuning Large Language Models (LLMs), (Llama, GPT, BERT, etc.).

Company Description About Sopra Steria Sopra Steria, a major Tech player in Europe with 50,000 employees in nearly 30 countries, is recognised for its consulting, digital services and solutions. It helps its clients drive their digital transformation and obtain tangible and sustainable benefits. The Group provides end-to-end solutions to make large companies and organisations more competitive by combining in-depth knowledge of a wide range of business sectors and innovative technologies with a collaborative approach. Sopra Steria places people at the heart of everything it does and is committed to putting digital to work for its clients in order to build a positive future for all. In 2024, the Group generated revenues of €5.8 billion. The world is how we shape it. Job Description Data Scientist : Robust knowledge of machine learning model development , including strong familiarity with classical ML techniques, both supervised and unsupervised approaches. Proficiency in Python , with a solid understanding of key data science packages such as scikit-learn, pandas, NumPy, xgboost, LightGBM, and nltk. Strong knowledge of SQL , ideally with experience in Snowflake’s SQL flavour. Familiarity with agile methodologies . Knowledge of version control and git-based workflows . Experience with Spark , particularly PySpark. Familiarity with cloud-based environments , with a focus on AWS, especially SageMaker. Total Experience Expected: 08-10 years Qualifications Professional Degree with Data Science experience Additional Information At our organization, we are committed to fighting against all forms of discrimination. We foster a work environment that is inclusive and respectful of all differences. All of our positions are open to people with disabilities.

We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Job Description We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Responsibilities Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Qualifications Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills

Company Description Beltech AI develops AI-driven solutions for smart traffic management, urban planning, and related sectors. We use computer vision , data analytics , and machine learning algorithms to create intelligent systems that can monitor, manage, and analyze traffic conditions in real-time. Role Description This is a full-time on-site Data Scientist role located in Bengaluru. The Data Scientist will be responsible for tasks such as data science, statistics, data analytics, creating algorithims to support the development of AI-driven solutions for smart infrastructure. Who We Are Looking For At Beltech AI, we value growth trajectory and impact over years of experience . Join us if you: Are driven by solving challenging, real-world problems—not just job titles. Thrive as a generalist eager to take on high-stakes, meaningful work. Are passionate about learning and pushing boundaries, with something exceptional to show for it. Understand how to make smart trade-offs and believe that speed and quality can go hand in hand. Are a strong team player who believes in fostering collective growth through empathy and collaboration Qualifications Data Science and Statistics skills Data Analytics, Data Visualization, and Data Analysis skills Experience in working with large datasets Proficiency in programming languages like Python or R Strong analytical and problem-solving skills Ability to work collaboratively in a team environment Bachelor degree or higher in Data Science, Maths, Computer Science, Statistics, or related field from Tier 1 Colleges ( IIT,NIT,IIIT)

About the Role Love deep data? Love discussing solutions instead of problems? Then you could be our next Data Scientist. In a nutshell, your primary responsibility will be enhancing the productivity and utilisation of the generated data. Other things you will do include working closely with the business stakeholders, transforming scattered pieces of information into valuable data and sharing and presenting your valuable insights with peers. What you will do Develop models and run experiments to infer insights from hard data Improve our product usability and identify new growth opportunities Understand reseller preferences to provide them with the most relevant products Designing discount programs to help our resellers sell more Help resellers better recognise end-customer preferences to improve their revenue Use data to identify bottlenecks that will help our suppliers meet their SLA requirements Model seasonal demand to predict key organisational metrics Mentor junior data scientists in the team What you will need Bachelor's/Master's degree in computer science (or similar degrees) 2-4 years of experience as a Data Scientist in a fast-paced organization, preferably B2C Familiarity with Neural Networks, Machine Learning, etc Familiarity with tools like SQL, R, Python, etc Strong understanding of Statistics and Linear Algebra Strong understanding of hypothesis/model testing and ability to identify common model testing errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analytical skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: Experience in working on personalization or other ML problems Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift

We are seeking an experienced and highly motivated Data Scientist with a strong background in backend development and AI/ML engineering. The ideal candidate will have solid experience in building, deploying, and scaling machine learning solutions using Python and modern ML frameworks. Key Responsibilities: Design, develop, and deploy machine learning models, including advanced architectures such as Large Language Models (LLMs). Collaborate with cross-functional teams to build scalable AI-driven solutions using robust software engineering principles. Leverage Python and object-oriented programming techniques to create efficient, maintainable, and production-grade ML pipelines. Work with popular machine learning frameworks such as TensorFlow , PyTorch , and Scikit-learn for model development and experimentation. Integrate AI/ML models into applications using RESTful APIs and ensure performance, scalability, and reliability. Utilize tools such as Hugging Face , LangChain , and OpenAI APIs to build and fine-tune NLP and generative AI models. Implement and manage containerized services using Docker , enabling smooth deployment and reproducibility of ML solutions. Apply best practices in version control (Git) and software development lifecycles to support collaborative and agile workflows. Design, develop, and maintain relational databases (e.g., MySQL , PostgreSQL , Oracle ) to support data-driven applications. Contribute to the design and implementation of microservices-based architectures for AI/ML systems. Understand and apply agent communication protocols and multi-agent system design (e.g., MCP) where relevant to AI applications. Analyze large datasets, derive actionable insights, and drive continuous model improvements. Required Skills and Qualifications: 4+ years of experience in data science, machine learning, or backend development roles. Proficiency in Python and strong foundations in object-oriented programming . Hands-on experience with machine learning model lifecycle — from training to production deployment and monitoring. Familiarity with scalable system design and microservices architecture. Excellent problem-solving skills, attention to detail, and a strong understanding of data structures and algorithms. Effective communication and collaboration skills, with the ability to work in a dynamic team environment. Preferred Qualifications: Generative AI Expertise: Practical experience and in-depth knowledge of Generative AI technologies, including Large Language Models (LLMs) such as GPT, LLaMA, and their real-world applications. Prompt Engineering & Model Optimization: Proficiency in prompt engineering, fine-tuning LLMs, and evaluating the performance and effectiveness of AI/ML models. AI System Architecture: Familiarity with orchestration frameworks and agent-based system architectures for building modular and intelligent AI solutions. Advanced AI Tooling: Experience working with and integrating state-of-the-art AI tools, platforms, and APIs into scalable systems. Innovation Mindset: Demonstrated ability to creatively apply AI/ML — including Generative AI and LLMs — to solve complex problems and deliver business value, especially in the payment technology or fintech domains. Cross-Functional Collaboration: Strong communication skills with a proven track record of working effectively in cross-disciplinary teams, including product, engineering, and data stakeholders. Responsible AI Practices: Knowledge of ethical AI principles, including model interpretability, fairness, responsible AI deployment, and ongoing model monitoring.

Company Description HCL Software is a division of HCL Technologies (HCL) that operates its primary software business. It develops, markets, sells, and supports over 20 product families in the areas of Customer Experience, Digital Solutions, Security & Automation and DevOps. Its mission is to drive ultimate customer success with their IT investments through relentless innovation of its products. As Data Scientist/Researchers you will be responsible for leveraging the established architecture disciplines to help ensure that business strategies align with powerful capabilities of AI/ML to achieve business objectives consistently and cost effectively. We are looking for experience of 10 to 15 years only. Please apply only if you match the experience level Location- Bangalore and Noida. Please share CV to monica_sharma@hcl-software.com with the below details: Total Experience- Current CTC- Expected CTC- Notice Period- Main Responsibilities Propose solutions and strategies to tackle business challenges in AI/ML product Operationalizing and architecting ML/AI solutions Qualifications, Education and Experience: Phd, Masters or Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, Mathematics with at least 10+ years in ML/AI Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains. Proven ability to rationalize disparate data sources and the ability to intuit the large picture within a dataset Experience in solving client's analytics problems and effectively communicating results and methodologies Software development skills in one or more scripting language preferably python, and common ML tools (Weka, R, RapidMiner, KNIME, scikit, AzureML, Sagemaker, ModelBuilder etc.) Familiarity with ML tools and packages like OpenNLP, Caffe, TensorFlow etc. Knowledge of MLOps pipeline Knowledge of machine learning and data mining techniques in one or more areas of statistical modeling methods Anomaly detection Regression, classification, clustering Deep learning Survival analysis Similarity and recommendation Forecasting Strong oral and written communication skills, including presentation skills Strong problem solving and troubleshooting skills

As an AI/ML Consultant, you will be responsible for designing and overseeing the architecture of AI and machine learning solutions. You will work closely with data scientists, engineers, and business stakeholders to ensure that our AI/ML initiatives are scalable, robust, and aligned with business objectives. Your expertise in machine learning, deep learning, natural language processing (NLP), and generative AI will be crucial in guiding the development and deployment of advanced AI solutions. Responsibilities: Design and architect end-to-end AI/ML solutions that meet business requirements and technical specifications. Develop and implement scalable machine learning and deep learning models, ensuring they integrate seamlessly into existing systems. Create architectures for NLP applications, including text processing, sentiment analysis, named entity recognition, and language modelling. Leverage generative AI and large language models (LLMs) to develop innovative applications. Collaborate with data engineers to design data pipelines and ensure data quality and accessibility. Provide technical leadership and guidance to data scientists and engineers throughout the development lifecycle. Evaluate and select appropriate AI/ML tools, frameworks, and technologies to meet project needs. Ensure best practices in AI/ML model development, including versioning, testing, and validation. Stay updated with the latest advancements in AI/ML technologies and incorporate them into architectural designs. Communicate complex AI/ML concepts and solutions effectively to non-technical stakeholders. Requirements: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. Proven experience (8+ years) in designing and implementing AI/ML solutions, with a strong focus on machine learning, deep learning, NLP, and generative AI. Extensive experience with machine learning algorithms, model development, and deployment. Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras. Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc. Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services. Knowledge of big data technologies and tools such as Hadoop, Spark, and Kafka. Proficiency in programming languages such as Python, R, and Java. Excellent problem-solving skills and the ability to design robust, scalable AI/ML architectures. Strong communication skills, with the ability to present technical concepts to both technical and non-technical audiences. Experience in leading and mentoring technical teams. Preferred Qualifications: Experience with MLOps practices and tools for continuous integration and deployment of machine learning models. Familiarity with data visualization tools such as Looker, Tableau, Power BI, or similar.

Fast API, Azure UI Search API (React) Cosmos DB (API for MongoDB), Data Factory Data Bricks Proficiency in Python and R Azure Cloud Basics (Azure DevOps) Gitlab End-to-end AI solution delivery AI integration and deployment

Key Responsibilities Business Understanding & Solutioning Engage with clients/stakeholders to define analytics roadmaps. Translate business problems into ML, DL, or GenAI-driven analytical solutions. Participate in pre-sales activities, including creating pitch decks, framing solutions, and presenting to clients. Modeling & AI Development Develop models for Prediction, Forecast, Segmentation, Churn, CLV, Recommendation Systems. Build Generative AI solutions using LLMs, Transformers, Autoencoders. Implement scalable AI/ML pipelines with MLOps tools (MLflow, Docker, CI/CD). Team Leadership & Collaboration Lead and mentor 5–10+ data scientists. Work with engineering, product, and client teams to integrate AI in workflows. Knowledge Sharing & Mindset Promote a learning culture; share knowledge across the team. Coach junior ML members and foster collaboration.

Company Description About Sopra Steria Sopra Steria, a major Tech player in Europe with 50,000 employees in nearly 30 countries, is recognised for its consulting, digital services and solutions. It helps its clients drive their digital transformation and obtain tangible and sustainable benefits. The Group provides end-to-end solutions to make large companies and organisations more competitive by combining in-depth knowledge of a wide range of business sectors and innovative technologies with a collaborative approach. Sopra Steria places people at the heart of everything it does and is committed to putting digital to work for its clients in order to build a positive future for all. In 2024, the Group generated revenues of €5.8 billion. The world is how we shape it. Job Description Data Scientist : Robust knowledge of machine learning model development , including strong familiarity with classical ML techniques, both supervised and unsupervised approaches. Proficiency in Python , with a solid understanding of key data science packages such as scikit-learn, pandas, NumPy, xgboost, LightGBM, and nltk. Strong knowledge of SQL , ideally with experience in Snowflake’s SQL flavour. Familiarity with agile methodologies . Knowledge of version control and git-based workflows . Experience with Spark , particularly PySpark. Familiarity with cloud-based environments , with a focus on AWS, especially SageMaker. Total Experience Expected: 08-10 years Qualifications Professional Degree with Data Science experience Additional Information At our organization, we are committed to fighting against all forms of discrimination. We foster a work environment that is inclusive and respectful of all differences. All of our positions are open to people with disabilities.

Key Skills: Machine Learning, Python, Power BI Roles and Responsibilities: Enthusiasm for building analytics and data science solutions while staying updated with latest trends. Strong analytical mindset with experience in building Data Science solutions. Proven experience solving business problems using Data & Analytics techniques. Strategic thinking with a strong customer focus. Ability to articulate complex issues and clearly communicate analytical outputs. Evidence-based decision making with solid analytical and documentation skills. Excellent verbal and written communication skills. Strong collaboration and interpersonal abilities. Innovative, adaptable, and quick to learn new skills and content. Proven ability to work closely with stakeholders and build collaborative partnerships. Ability to convey complex data and analytics to business stakeholders effectively. Strong task management and self-organization skills. Key Accountabilities: Lead the use of advanced analytics across marketing use cases to support data-driven strategy. Enhance feature stores and apply robust feature engineering for marketing analytics. Leverage online data sources (e.g., Adobe Analytics) for marketing applications. Deliver against the AI/ML roadmap for marketing in alignment with enterprise platform capabilities. Drive the continuous improvement and adoption of advanced analytics across teams. Present insights to senior stakeholders using visualization tools and insightful presentations. Develop advanced analytic techniques to support customers' unmet financial needs. Skills Required: 4-6 years of experience in the data science field. Leading the build and deployment of machine learning models to achieve business outcomes. Proficiency in SQL, Python, PySpark, Spark ML. Working knowledge of cloud platforms such as AWS (preferred), Azure, or GCP. Proficient in using source code control tools such as GitHub. Experience working with structured and unstructured datasets and applying advanced analytics techniques. Familiarity with customer data, digital data, and the analytics landscape, with the ability to provide insights for business decision making. Hands-on experience with AutoML tools like DataRobot or H2O.ai. Ability to explore new methodologies to collaboratively solve business challenges. Strong stakeholder management and influencing skills to shape the data science backlog. Strong communication skills to simplify and present complex analytics. Experience with data visualization tools to share insights effectively with stakeholders. Desirable Experience: Leading use of advanced analytics in marketing for strategic data-driven decisions. Contributing to the Artificial Intelligence (AI) roadmap for marketing based on architecture and delivery timelines. Promoting continuous improvement in the adoption and application of advanced analytics. Presenting analytical insights via visual tools and professional insight presentations. Developing new or enhanced analytics techniques to uncover and support unmet customer financial needs. Education: Bachelor's or Postgraduate degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or other relevant disciplines.

Job Title: Data Scientist Location: Bangalore, Chennai, Hyderabad, Pune Experience: 4-10 Years Job Deescription As a Senior Data Scientist, you will lead the development and optimization of advanced analytics tools, with a focus on media intelligence solutions. Your work will involve analyzing large data sets from various media channels, designing algorithms to track trends, and providing actionable insights. We are looking for someone with a strong background in building media analytics or intelligence tools, combined with excellent problem-solving skills and a passion for innovation. Required Skills And Qualifications Proven experience (7+ years) as a Data Scientist, preferably in the media intelligence or analytics tool development domain. Strong expertise in machine learning, NLP, and statistical modeling. Gen AI technologies usage like ChatGPT, OpenAI, LLM Technologies Hands-on experience with media data analysis, including sentiment analysis, keyword analysis, and audience engagement tracking. Proficiency in Python, R, and SQL. Familiarity with big data tools such as Hadoop, Spark, Redis, Apache Flink, and cloud platforms (AWS, GCP, Azure). Strong understanding of data pipelines and experience with data processing frameworks. Ability to work with large, unstructured data sets and develop models that derive actionable insights. Excellent problem-solving skills and the ability to deliver solutions in a fast-paced environment. Strong communication and presentation skills, with the ability to explain complex data insights to non-technical stakeholders. A Master's or PhD in Data Science, Computer Science, Statistics, or a related field. Preferred Skills: Experience with media monitoring, social listening, or media analytics platforms. Experience in deploying machine learning models in production environments. Familiarity with media intelligence tools such as Meltwater, Cision, or similar. Roles & Responsibilities: Lead the design and development of analytics platforms and media intelligence tools, transforming large, unstructured data into meaningful insights. Develop machine learning models for trend detection, sentiment analysis, keyword extraction, and content recommendation. Work with large-scale media data from sources such as social media, news, blogs, and other online platforms. Collaborate with cross-functional teams, including data engineers, software developers, and product managers, to deliver end-to-end solutions. Implement NLP techniques to analyze and categorize media content from multiple sources. Build and optimize data pipelines for efficient data processing, storage, and retrieval. Translate business objectives into data-driven solutions and deliver actionable insights to internal teams and clients. Mentor and guide junior data scientists, providing support in developing their technical skills and career growth. Stay updated on the latest trends in data science, AI, and media intelligence to ensure the tools and platforms remain at the cutting edge.

Entity: Technology Job Family Group: IT&S Group Job Description: Data Scientist / Machine Learning Engineer Responsible for supporting the delivery of business analysis and consulting processes and procedures for the defined specialism using sound technical capabilities, building and maintaining effective working relationships, ensuring relevant standards are defined and maintained, and supporting delivery of process and system improvements. Specialisms: Business Analysis; Data Management and Data Science; Digital Innovation. India - Pune Job Description Being part of the P&O Digital Delivery data group, you will apply your experience and familiarity with domain data processes to support the P&O organisation across teams such as Wells & Subsurface, Production and bp Solutions. These teams provides daily operational data management, data engineering and analytics support to this organisation across a broad range of disciplines, applications and business requirements. Let me tell you about the role A data scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Their key responsibilities include collecting and analyzing large sets of data, using machine learning algorithms, statistical models, and data processing techniques to predict future trends and provide actionable insights. A machine learning engineer designs and develops artificial intelligence (AI) systems that can learn and make decisions autonomously. Their key responsibilities include creating and optimizing machine learning models, developing algorithms that enable machines to perform tasks without explicit programming, and working with large datasets to train these models. They collaborate with data scientists, software engineers, and domain experts to implement machine learning solutions that address specific business needs. Additionally, machine learning engineers are responsible for ensuring the scalability and efficiency of machine learning systems, continuously improving model performance through rigorous testing and validation, and staying updated with the latest advancements in the field to integrate cutting-edge techniques into their work. What you will deliver Part of a cross-disciplinary team, working closely with other data scientists, data engineers software engineers, data managers and business partners. Build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Carry out data analyses to yield actionable business insights. Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation). Present results to peers and senior management. Actively contributes to improve developer velocity. Mentor others. What you will need to be successful (experience and qualifications) Essential MSc or PhD degree in a quantitative field. Hands-on experience designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Applied knowledge as part of a team (if not leading) of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Basic SQL knowledge. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Strong stakeholder management and ability to lead large organizations through influence. Continuous learning and improvement mindset. Desired Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus. Knowledge of experimental design and analysis is a plus. Familiarity and experience with common Energy domain data objects and formats About Bp Our purpose is to deliver energy to the world, today and tomorrow. For over 100 years, bp has focused on discovering, developing, and producing oil and gas in the nations where we operate. We are one of the few companies globally that can provide governments and customers with an integrated energy offering. Delivering our strategy sustainably is fundamental to achieving our ambition to be a net zero company by 2050 or sooner! Travel Requirement Up to 10% travel should be expected with this role Relocation Assistance: This role is eligible for relocation within country Remote Type: This position is a hybrid of office/remote working Skills: Data Management, Data Science, Machine Learning, Machine Learning Algorithms Legal Disclaimer: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us. If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

Job Summary: We are seeking a highly skilled and forward-thinking Data Scientist with expertise in automation solutions powered by Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Vision-Language Models (vLMs) and production level deployment experience on azure Cloud. The ideal candidate will bridge the gap between business needs and technical capabilities, driving intelligent automation initiatives across the organization. Key Responsibilities: Collaborate with stakeholders to gather and analyze business requirements for automation use cases. Design and document intelligent automation workflows using AI/ML technologies. Work closely with data scientists, ML engineers, and developers to implement solutions using: o Computer Vision for image/video analysis. o LLMs for natural language understanding and generation. o OCR for document digitization and data extraction. o vLMs for multimodal data interpretation. o Agents: Orchestration tools like langraph or autogen Define KPIs and success metrics for automation projects. Conduct feasibility studies and cost-benefit analyses. Ensure seamless integration of AI models with Azure Cloud services (e.g., Azure Cognitive Services, Azure ML, Azure Functions). Support testing, validation, and deployment of automation solutions. Provide training and documentation for end-users and stakeholders. Required Skills & Qualifications: Bachelor//'s or Master//'s degree in Computer Science, Engineering, Data Science, or related field. 4+ years of experience as a Business Analyst in tech-driven environments. Proven experience in automation projects involving AI/ML technologies. Strong understanding of: o Computer Vision frameworks (e.g., OpenCV, YOLO, Detectron2). o LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face Transformers). o OCR tools (e.g., Tesseract, Azure Form Recognizer, ABBYY). o vLMs (e.g., CLIP, Flamingo, GPT-4V). Hands-on experience with Azure Cloud services and DevOps practices. Excellent analytical, communication, and stakeholder management skills.

Role Definition: Data Scientists focus on researching and developing AI algorithms and models. They analyse data, build predictive models, and apply machine learning techniques to solve complex problems Skills Proficient: Languages/Framework: Fast API, Azure UI Search API (React) Databases and ETL: Cosmos DB (API for MongoDB), Data Factory Data Bricks Proficiency in Python and R Cloud: Azure Cloud Basics (Azure DevOps) Gitlab: Gitlab Pipeline Ansible and REX: Rex Deployment Data Science: Prompt Engineering + Modern Testing Data mining and cleaning ML (Supervised/unsupervised learning) NLP techniques, knowledge of Deep Learning techniques include RNN, transformers End-to-end AI solution delivery AI integration and deployment AI frameworks (PyTorch) MLOps frameworks Model deployment processes Data pipeline monitoring Expert: (in addition to proficient skills) Languages/Framework: Azure Open AI Data Science: Open AI GPT Family of models 4o/4/3, Embeddings + Vector Search Databases and ETL: Azure Storage Account Expertise in machine learning algorithms (supervised, unsupervised, reinforcement learning) Proficiency in deep learning frameworks (TensorFlow, PyTorch) Strong mathematical foundation (linear algebra, calculus, probability, statistics) Research methodology and experimental design Proficiency in data analysis tools (Pandas, NumPy, SQL) Strong statistical and probabilistic modelling skills Data visualization skills (Matplotlib, Seaborn, Tableau) Knowledge of big data technologies (Spark, Hive) Experience with AI-driven analytics and decision-making systems Skills: statistical modelling,data scientist,fastapi,nlp techniques,azure cloud basics,cosmos db,azure,ansible,sql,cosmos db (api for mongodb),unsupervised learning,gitlab pipeline,azure ui search api (react),reinforcement learning,modern testing,python,rex deployment,end-to-end ai solution delivery,ai-driven analytics,azure storage account,azure devops,open ai gpt family of models,transformers,data factory data bricks,numpy,data bricks,azure open ai,prompt engineering,etl,data pipeline monitoring,fast api,data factory,model deployment processes,tensorflow,data visualization (matplotlib, seaborn, tableau),pandas,ai integration and deployment,big data technologies (spark, hive),supervised learning,r,rnn,mlops frameworks,data mining and cleaning,pytorch,deep learning techniques

About Yubi Yubi, formerly known as CredAvenue, is redefining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plentiful, and we equip you with the tools to seize them. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest, and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset-based securitization Spocto - Debt recovery & risk mitigation platform Accumn - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals, and Predictions to Lenders, Investors, and Business Enterprises So far, we have onboarded over 17,000+ enterprises and 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed, and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come join the club to be a part of our epic growth story. About the job Job Title: Data Scientist 2 (LLM/GenAI) Location: Bangalore Experience: 2 - 4 years Employment Type: Full-time Job Summary: We seek a highly skilled Data Scientist (LLM) to join our AI and Machine Learning team. The ideal candidate will have a strong foundation in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) , along with hands-on experience in building and deploying conversational AI/chatbots . The role requires expertise in LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . You will work closely with cross-functional teams to drive the development and enhancement of AI-powered applications. Key Responsibilities: Develop, fine-tune, and deploy Large Language Models (LLMs) for various applications, including chatbots, virtual assistants, and enterprise AI solutions. Build and optimize conversational AI solutions with at least 1 year of experience in chatbot development. Implement and experiment with LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . Design and develop ML/DL-based models to enhance natural language understanding capabilities. Work on retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to enhance LLM-based applications. Optimize and fine-tune transformer-based models such as GPT, LLaMA, Falcon, Mistral, Claude, etc., for domain-specific tasks. Develop and implement prompt engineering techniques and fine-tuning strategies to improve LLM performance. Work on AI agents, multi-agent systems, and tool-use optimization for real-world business applications. Develop APIs and pipelines to integrate LLMs into enterprise applications. Research and stay up-to-date with the latest advancements in LLM architectures, frameworks, and AI trends . Required Skills & Qualifications: 2-4 years of experience in Machine Learning (ML), Deep Learning (DL), and NLP-based model development. Hands-on experience in developing and deploying conversational AI/chatbots is Plus Strong proficiency in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers . Experience with LLM agent development frameworks like LangChain, LlamaIndex, AutoGen, LangGraph . Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) and embedding models . Understanding of Prompt Engineering and Fine-tuning LLMs . Familiarity with cloud services (AWS, GCP, Azure) for deploying LLMs at scale. Experience in working with APIs, Docker, FastAPI for model deployment. Strong analytical and problem-solving skills. Ability to work independently and collaboratively in a fast-paced environment. Good to Have: Experience with Multi-modal AI models (text-to-image, text-to-video, speech synthesis, etc.) . Knowledge of Knowledge Graphs and Symbolic AI . Understanding of MLOps and LLMOps for deploying scalable AI solutions. Experience in automated evaluation of LLMs and bias mitigation techniques . Research experience or published work in LLMs, NLP, or Generative AI is a plus. Why Join Us? This is an opportunity to work on cutting-edge LLM and Generative AI projects . Collaborative and innovative work environment. Competitive salary and benefits. Career growth opportunities in AI and ML research and development.

This role is for one of the Weekday's clients Salary range: Rs 2000000 - Rs 3000000 (ie INR 20-30 LPA) Min Experience: 3 years Location: Bengaluru JobType: full-time We are seeking a highly motivated and results-driven Data Scientist with 3 to 6 years of experience to join our growing data science team. In this role, you will work at the intersection of business and technology, transforming raw data into actionable insights and intelligent models that drive strategic decision-making. Your deep understanding of machine learning algorithms, strong command over Python, and proficiency in SQL will be critical to solving complex business problems and enabling data-driven innovation across the organization. Requirements Key Responsibilities: Develop, implement, and optimize machine learning models to solve real-world business problems such as customer segmentation, recommendation systems, predictive analytics, churn prediction, and more. Translate business requirements into analytical models and data products that align with company goals. Clean, preprocess, and manipulate large datasets from various structured and unstructured sources using Python and SQL. Build data pipelines and automate data workflows for scalable model deployment and monitoring. Collaborate closely with cross-functional teams including data engineering, product, marketing, and operations to define problem statements, prioritize tasks, and deliver solutions. Present findings, models, and recommendations to both technical and non-technical stakeholders through clear visualizations and storytelling. Continuously research and stay updated on the latest trends in machine learning, statistical modeling, and data science techniques to apply best practices and enhance model performance. Ensure the reliability, accuracy, and explainability of models, and participate in code reviews, model validation, and documentation. Skills and Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field. 3 to 6 years of hands-on experience in data science or machine learning roles. Strong proficiency in Python and its data science libraries (such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, TensorFlow or PyTorch). Solid experience with SQL for data querying, manipulation, and aggregation across large datasets. Demonstrated ability to build and deploy end-to-end machine learning models in production environments. Strong understanding of statistical analysis, data modeling, and algorithm design. Experience working with large-scale datasets, preferably in cloud environments (AWS, GCP, or Azure). Familiarity with tools like Jupyter Notebooks, Git, and CI/CD pipelines is a plus. Excellent problem-solving, critical thinking, and communication skills. Ability to work independently in a fast-paced, dynamic environment while collaborating effectively within a team

We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

🌟 Title: Data Scientist 📍 Location: Sector-48, Sohna Road, Gurgaon (Gurugram) - 122018 💼 Type: Hybrid – 3 days per week in Gurugram office 🚀 Start Date: Immediate (need someone who can join within 15 days or less) 💰 Compensation: 30-35 LPA (100% fixed) + benefits **Benefits include: 11 National Holidays and 15 PTO days Health Insurance: 30 Lakh for employee, spouse, two dependent children, and two parents/in-laws Accident & Disability: 50 Lakh for employee Free doctor consultations Key Requirements Must be able to work hybrid in Gurugram office 3 days per week Must be ready to join immediately within 15 days Must Haves: 5+ years of experience as a data scientist Statistics or mathematics background/degree Strong technical experience with Snowflake, Azure, Databricks, Python and SQL Plusses: Med device, healthcare, or pharmaceutical background Description: An employer is seeking an experienced Data Scientist based in Gurgaon, India to join an analytics organization for a global medical device client. This individual will support a major compliance initiative and serve as lead data scientist overseeing algorithm buildouts. They will be collaborating with the data engineering team to source and clean the data. They will also work closely with stakeholders to understand the specific requirements and will create algorithms based off of those specifications. The technology landscape includes: Databricks, Python, SQL, Snowflake and Azure.