Data Scientist - F2F discussion - Chennai

Tata Consultancy Services; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Tata Consultancy Services is seeking a Data Scientist to design and deploy ML, DL and GenAI solutions for business challenges. You will perform EDA, feature engineering, and model optimization while collaborating with data engineers and product teams.

Responsibilities include building AI-powered systems using LangChain, LLMs, and cloud platforms, ensuring performance, explainability, and production reliability. Mentoring junior scientists and staying ahead of AI trends are also expected.

Qualifications

• Experience building ML/GenAI solutions for business problems.
• Proficient in data wrangling, profiling, and feature engineering.
• Hands-on with model training, evaluation, and deployment.

Responsibilities

• Develop and deploy ML, DL, and GenAI solutions.
• Perform EDA, data profiling, and feature engineering to derive insights.
• Build, train, validate, and optimise predictive models.
• Design GenAI apps using LLMs, Prompt Engineering, RAG, AI Agents.
• Develop AI-powered solutions with LangChain, LangGraph, OpenAI, Gemini.
• Work with Azure, AWS, or GCP for scalable AI deployments.
• Implement MLOps for deployment, monitoring, governance, lifecycle.

Skills

Machine Learning

Deep Learning

GenAI

EDA

Feature Engineering

Model Deployment

MLOps

Explainability

Collaboration

Mentoring

Tools

LangChain

LangGraph

OpenAI

Gemini

Azure

AWS

GCP

Job description

Greetings from Tata Consultancy Services (TCS)

What we are looking for : Data Scientist

Interview Mode : F2F discussion

Experience : 5-15 Years

• Develop and deploy Machine Learning, Deep Learning, and Generative AI solutions to address complex business challenges.
• Perform exploratory data analysis (EDA), data profiling, and feature engineering to derive meaningful insights from large datasets.
• Build, train, validate, and optimise predictive models using statistical and machine learning techniques.
• Design and implement GenAI applications using LLMs, Prompt Engineering, RAG, and AI Agent frameworks.
• Develop AI-powered solutions leveraging LangChain, LangGraph, OpenAI, Gemini, and other modern AI ecosystems.
• Work with cloud platforms such as Azure, AWS, or GCP to build scalable and production-ready AI solutions.
• Implement MLOps practices for model deployment, monitoring, governance, and lifecycle management.
• Collaborate with business stakeholders, data engineers, architects, and product teams to translate business requirements into AI solutions.
• Ensure model performance, explainability, responsible AI practices, security, and production reliability.
• Mentor junior data scientists, drive innovation, and stay updated with emerging trends in AI, ML, GenAI, and data science technologies.