Top Data Science Jobs in Chennai

Lead product strategy and roadmap for AI-driven onboarding experiences. Translate customer needs into product requirements, partner with engineering/design/data science, run discovery through launch, and use data and A/B experiments to iterate and optimize user-centric workflows.

Lead end-to-end strategic supply chain projects and cross-functional teams to design and implement global supply chain architectures. Apply advanced analytics and financial modeling to identify improvements, consult executives on risk and growth, and develop frameworks, tools, and long-term supply chain strategies from planning through execution.

Lead and manage customer analysis deep dives, execute strategies from senior leadership, manage client communication, and mentor analysts.

Lead and manage customer analysis, mentor analysts, apply data science methods for insights, manage data science projects, and communicate findings.

Design, develop, and deploy production-ready AI/ML and Generative AI solutions. Requires strong foundation in data science, machine learning, neural networks, and deep learning. Must have a relevant degree and 4-6 years of ETL or data management experience.

The Data Scientist will analyze and model data for ML systems, focusing on Personalization and Recommendation Engines, and collaborate with teams to enhance data-driven solutions.

As an Associate Product Manager, you will manage product development cycles, collaborate with engineering and operational teams, evaluate partnerships, and prioritize projects to improve customer adoption.

The Senior Data Scientist will enhance the predictive modeling capabilities of Lyric's platform, focusing on machine learning and statistical methods for supply chain optimization.

Senior Executive to lead client relationships, shape EXL's data and analytics strategy, drive generative AI adoption, oversee delivery and growth across industries, and represent the firm with C-suite clients.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Lead insights and analysis for assigned clients by applying data science methods, managing multiple analytics engagements, preparing and integrating datasets, communicating findings, and developing the analytics team through training and escalation management.

Lead insights and analysis for assigned clients by applying data science methods, managing multiple analytics engagements, preparing and integrating datasets, communicating findings, and developing the team through training and objectives.

Lead design and delivery of end-to-end AI/ML and Generative AI solutions, architect scalable cloud-based platforms, integrate LLM/RAG/agentic systems, implement MLOps and governance, and mentor teams while driving AI strategy with stakeholders.

Lead development and deployment of marketing measurement models (MMM, incrementality, forecasting) using Bayesian methods; partner with AI agents and engineering to operationalize agentic analytics, deliver client-ready insights, train teams, and mentor junior data scientists.

Lead development and deployment of marketing measurement models (MMM, incrementality, forecasting) using Bayesian methods. Collaborate with AI Agents and Data Engineering to build scalable, client-facing solutions, validate tools, train teams, produce client deliverables, and mentor junior data scientists.

Lead development and deployment of marketing measurement models (MMM, incrementality, forecasting) using Bayesian methods. Partner with AI Agents and Data Engineering to productionize agentic analytics, validate deployed tools, train teams, mentor juniors, and produce client-ready insights and GTM recommendations.

Lead development and deployment of marketing measurement models (MMM, incrementality, forecasting) using Bayesian methods; partner with AI Agents and Data Engineering to productionize models, create client deliverables, train teams, mentor junior scientists, and establish scalable methodology.

Lead design, development, and deployment of multi-agent, agentic AI solutions using LangGraph, LLM orchestration, RAG, and RL-based fine-tuning. Build scalable architectures, integrate vector databases and knowledge graphs, run PoCs to demonstrate business impact, and mentor AI engineers and data scientists for production-grade autonomous agents.

Lead research, design, and deployment of multi-agent, agentic AI systems using LangGraph and LLM orchestration. Build memory-augmented agents, implement RAG with vector DBs, apply RLHF/RLAIF, prototype PoCs, scale production architectures, and mentor AI engineers.

Lead clinical data management across trials ensuring data integrity, regulatory compliance, inspection readiness, and delivery of CRFs, datasets, and review plans. Collaborate with cross-functional teams and vendors, define eCRF/data requirements, provide team leadership, training, and continuous improvement.

Lead an AI-first transformation of procurement operations: assess Source-to-Pay maturity, design automation and LLM data governance, select and deploy S2P and CLM technologies, implement RPA/ML solutions, enable high-fidelity spend categorization and supplier compliance automation, and drive stakeholder integration and change management with IT and executive leadership.

Lead architecture, development, deployment, and scaling of LLM, NLP, and Computer Vision solutions. Build RAG, prompt engineering, fine-tuning, multimodal AI, and production ML pipelines. Mentor data scientists, drive AI strategy, ensure model governance, and collaborate with product, engineering, and business stakeholders to deliver enterprise AI systems.

Deliver live instruction, on-demand tutoring, video explanations, and QA reviews for Data Analytics learners. Mentor new experts, maintain QA standards (≥80%), contribute curriculum updates, and support learner engagement and academic quality improvements.

As a Clinical Data Science Programmer, you will develop and validate programming code for clinical trials, ensuring data integrity and compliance with regulatory standards while collaborating with scientists and statisticians.

Lead design and delivery of NLP and Generative AI solutions, from problem definition through deployment. Build and fine-tune transformers and LLMs for summarization, QA, classification and chatbots, apply classical and deep learning methods, ensure scalable reproducible ML workflows in cloud environments, mentor junior data scientists, and collaborate with product and engineering to translate business problems into AI solutions.