Lead Data Scientist

Lead Data Scientist – Agentic AI & Advanced Machine Learning

Experience : 6–7 Years Location : Hyderabad

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 good 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

• 6–7 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.