Top Data Science Jobs in Chennai

Design and model application data architecture, build scalable data pipelines and storage, integrate data systems, and operationalize AI/ML models. Lead teams, define standards, mentor juniors, and collaborate with business and engineering stakeholders to deliver production-ready AI solutions.

Design and model application data architecture, build scalable data pipelines, operationalize AI/ML solutions (including LLMs and Deep Learning), ensure data storage/integration, lead teams, mentor juniors, and collaborate with business and engineering stakeholders to deliver production-ready ML systems.

Design and model application data architecture, build scalable data pipelines, and operationalize AI/ML solutions. Customize and deploy deep learning and generative AI models, integrate LLMs, ensure data storage and retrieval efficiency, collaborate with cross-functional teams, mentor junior staff, and drive data architecture standards and best practices to meet business requirements.

Develop production-ready AI/ML applications using cloud AI services and generative models. Design and implement ML pipelines, work on deep learning, chatbots, and image processing, collaborate cross-functionally, lead and mentor team members, and improve processes for scalable deployment.

Design and model application data architecture, storage and integration. Build scalable data pipelines and MLOps for production ML/AI solutions, customize deep learning and LLM models, collaborate with stakeholders, lead teams, and mentor juniors to align data strategies with business needs.

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.

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.

Lead product strategy and roadmap for Compass, an in-store navigation and personalization product. Collaborate with engineering, data science, design, and analytics to define data models, optimize recommendation models, run experiments (A/B, DiD), and deliver personalized experiences that improve associate and customer item discovery and business metrics.

Lead delivery of scalable intelligent automation and agentic AI solutions for Finance: own product portfolio, identify/prioritize use cases, manage end-to-end delivery, realize value metrics, lead team and vendors, and ensure governance, scalability, and enterprise alignment.

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 and optimize end-to-end chargeback operations, driving strategic planning, process improvements, and SLA management. Oversee cross-functional teams, integrate data science into dispute workflows, ensure compliance and risk controls, deliver client-facing reporting, and maintain SOPs/SOWs to improve efficiency, quality, and revenue recovery.

Lead and mentor Predictive and Causal AI teams, architect end-to-end ML/GenAI solutions (including RAG and agentic frameworks), drive MLOps and cloud deployments, prototype POCs to demonstrate ROI, consult global stakeholders, and shape center-level AI product strategy and talent programs.

Lead and manage the Data Science team delivering MMM, incrementality, RBA, and forecasting models. Oversee end-to-end model development, validation, productization, API design for agent consumption, mentor staff on Bayesian and causal methods, and coordinate with Data Architecture and Media Effectiveness teams.

Lead and deliver measurement and marketing-science models (MMM, incrementality, RBA, forecasting); manage model pipelines, validate methodology, productize agentic models, mentor data scientists, coordinate with data architecture, and support GTM for analytics products.

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 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 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 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 data science projects: analyze banking data, build ML solutions, design data displays, consult with stakeholders, manage requirements-to-implementation, coach junior staff, and ensure compliance and data quality.

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.

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.