Core Programming &

- Tools

- Hands-on experience building and deploying ML models on large-scale production datasets

- Robust programming proficiency in Python with production-quality, well-structured code

- Proficient in SQL;

experience working with large-volume datasets in Spark and/or Snowflake

- Experience with Git for version control, code review, and collaboration

- Familiarity with experiment tracking and model versioning (e.g., MLflow)

Classical ML &

- Statistical Modeling

- Time series forecasting (ARIMA, Prophet, deep learning approaches)

- Optimization modeling (linear programming, mixed-integer programming)

- Classification, regression, clustering, and ensemble methods

- Feature engineering, data wrangling, and statistical analysis on structured data

LLM Application &

- AI Agent Development

- AI Agent development:



experience building agentic frameworks using Azure AI Studio and Azure model endpoints, including tool-use patterns and multi-step orchestration

- RAG pipeline development: document ingestion/chunking, vector embedding/indexing (Azure AI Search), and response generation using LLM endpoints

- Prompt engineering and chain-of-thought design for complex supply chain workflows

- Experience with orchestration frameworks like LangChain or LlamaIndex

Azure &

- Production Delivery

- Familiar with core Azure resources: Azure Machine Learning, Azure AI Studio, Azure OpenAI Service, and Azure storage/compute

- Experience delivering production-ready models with proper testing, validation, and monitoring

- Basic UI skills (Streamlit or Gradio) for quick prototyping and demos

📌 Data Science/Data Scientist (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru