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
Solid 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.

📌 Senior Data Scientist (AI/ML) (Secunderabad)
🏢 Providence India
📍 Secunderabad