Data Scientist

Job Description – Data Scientist | GenAI & Agentic AI

Position: Data Scientist

Experience: 4–8 Years

Location: Chennai

Work Mode: Work from Office

Job Summary

We are looking for a skilled Data Scientist with a strong foundation in Machine Learning, Statistical Analysis, and Data-Driven Problem Solving, along with hands-on experience in Generative AI and Agentic AI development.

The ideal candidate will have experience building and deploying LLM-powered applications and should be comfortable working with Prompt Engineering, Retrieval-Augmented Generation (RAG), Embeddings, Vector Databases, Tool/Function Calling, and Multi-Agent/Agentic Workflows.

This role requires someone who can combine strong traditional Data Science expertise with modern GenAI capabilities to design, develop, evaluate, and deploy AI solutions from experimentation through production.

Key Responsibilities

Develop and implement machine learning and statistical models to solve business problems.

Design and build Generative AI applications using Large Language Models (LLMs).

Develop RAG-based solutions using embeddings, vector databases, document retrieval, and contextual generation.

Implement effective prompt engineering strategies for LLM-based applications.

Build AI agents and multi-step agentic workflows using tool/function calling and orchestration frameworks.

Integrate LLM applications with enterprise data sources, APIs, databases, and existing business applications.

Design and implement scalable AI/ML solutions suitable for production environments.

Develop evaluation frameworks to assess LLM accuracy, relevance, reliability, latency, and overall application performance.

Implement appropriate AI guardrails, validation mechanisms, and responsible AI practices.

Perform data analysis, feature engineering, model development, validation, and optimization.

Collaborate with engineering, product, and business teams to translate requirements into data and AI solutions.

Troubleshoot and optimize AI/ML applications for performance, scalability, cost, and reliability.

Contribute to the deployment, monitoring, and continuous improvement of AI solutions in production.

Required Skills

Data Science & Machine Learning

Strong understanding of Machine Learning concepts and algorithms.

Strong foundation in Statistics, Probability, Data Analysis, and Predictive Modeling.

Hands-on experience with Python and relevant Data Science/ML libraries.

Experience with data preprocessing, feature engineering, model evaluation, and optimization.

Good understanding of supervised and unsupervised learning techniques.

Generative AI & LLM

Hands-on experience working with Generative AI and Large Language Models (LLMs).

Strong understanding of Prompt Engineering and LLM application development.

Practical experience with RAG (Retrieval-Augmented Generation).

Experience with Embeddings and Vector Databases.

Experience implementing Tool/Function Calling.

Understanding of LLM evaluation, hallucination mitigation, guardrails, and response validation.

Agentic AI

Experience designing and developing AI agents and agentic workflows.

Understanding of multi-step reasoning and workflow orchestration.

Experience integrating agents with APIs, enterprise systems, databases, and external tools.

Familiarity with agent orchestration frameworks is an advantage.

Deployment & Integration

Experience taking AI/ML solutions from prototype to production.

Understanding of APIs, microservices, cloud platforms, and application integration.

Knowledge of MLOps/LLMOps, monitoring, scalability, and production deployment is preferred.

Experience working with enterprise data sources and integrating AI solutions into existing applications.

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

4–8 years of relevant experience in Data Science, Machine Learning, AI, or related areas.

Experience working on end-to-end AI/ML projects.

Exposure to cloud platforms such as AWS, Azure, or GCP.

Familiarity with modern GenAI/LLM frameworks and AI development tools.

Strong analytical, problem-solving, communication, and collaboration skills.