Job Summary

We are looking for a highly skilled Lead Data Scientist with strong expertise in Agentic AI, Generative AI, Machine Learning, Deep Learning, NLP, RAG architectures, Azure AI ecosystem, and Statistical Modeling . The ideal candidate will lead the design and deployment of enterprise AI solutions, build advanced AI agents, develop LLM-powered applications, and drive data science initiatives from ideation to production.

This role requires a balance of hands-on technical expertise, problem-solving ability, and leadership in delivering business-impacting AI solutions.

Key Responsibilities

Agentic AI & Generative AI

- Design and develop AI agents and multi-agent systems using:
- LangGraph
- Semantic Kernel
- LangChain
- Develop Machine learning models, MMM models, and good in Analytical thoughts
- Very valuable at SQL coding as well, Knowledge in Snowflake is add on.
- Implement tool calling, reasoning workflows, memory management, and agent orchestration.
- Evaluate and optimize agent performance, grounding, accuracy, and reliability.

Retrieval-Augmented Generation (RAG)

- Design and implement enterprise-grade RAG solutions.
- Build knowledge retrieval pipelines using:
- Azure AI Search
- Vector Databases
- Embedding Models
- Optimize chunking, indexing, retrieval, reranking, and prompt engineering strategies.
- Experience with Graph RAG and Agentic RAG is preferred.

Machine Learning & Deep Learning

- Can write production grade SQL
- Build and deploy models for:
- Classification
- Regression




- Forecasting
- Recommendation Systems
- Anomaly Detection
- Develop deep learning solutions using:
- PyTorch
- TensorFlow
- Keras
- Perform feature engineering, model tuning, validation, and performance optimization.

NLP & LLMs

- Develop NLP solutions involving:
- Text Classification
- Entity Extraction
- Semantic Search
- Conversational AI
- Sentiment Analysis

Statistics & Analytics

Strong understanding of

- Probability & Statistics
- Hypothesis Testing
- A/B Testing
- Regression Analysis
- Bayesian Statistics
- Time Series Forecasting
- Experimental Design
- Statistical Inference
- Feature Selection Techniques

MLOps / LLMOps

- Build and deploy scalable AI solutions.
- Create CI/CD pipelines for ML models.
- Implement model monitoring, evaluation, and governance.
- Experience with:
- MLflow
- Docker
- Kubernetes
- GitHub Actions
- Azure DevOps

Experience

- 6–9 years of experience in Data Science and Machine Learning.
- Hands on SQL pipelines for deployment
- 3+ years of experience working on Generative AI solutions.
- Hands-on experience building RAG and LLM-based applications.
- Experience deploying AI solutions on Azure Cloud.
- Experience mentoring junior data scientists and leading technical initiatives.

Nice to Have

- Knowledge of GraphRAG.
- Fine-tuning open-source LLMs.
- Knowledge of Responsible AI and AI Governance.
- Azure AI Engineer Certification.
- Experience building enterprise AI Copilots.

📌 Lead Data Scientist (Hyderabad)
🏢 Providence India
📍 Hyderabad