Role: Senior Data Scientist - Experience Data & AI

Experience: 7 - 12 Years

Location: Pune

Role Overview:

We are seeking a Senior Data Scientist with deep expertise in advanced analytics, machine learning, and modern AI systems, including Large Language Models (LLMs) and AI Agents. This role is critical to designing and delivering intelligent, scalable, and explainable AI solutions across the enterprise by leveraging Microsoft AI Platform, Google AI Platform, Dataiku AI Platform, and Microsoft Copilot & Microsoft Fabric AI Platform.

Key Responsibilities:

AI & Advanced Analytics:

- Design, develop, and deploy end-to-end data science and AI solutions using classical ML, deep learning, and LLM-based architectures.

- Apply statistical modeling, hypothesis testing, optimization, and applied mathematics to solve complex business and engineering problems.

- Evaluate, fine-tune, and operationalize state-of-the-art LLMs across multiple platforms.

AI Agents & Autonomous Systems:

- Implement AI Agents using Agent-to-Agent (A2A) communication patterns.

- Build agent systems compliant with MCP (Model Context Protocol) for modularity, interoperability, and enterprise readiness.

- Orchestrate multi-agent workflows integrating tools, APIs, data sources, and LLM reasoning.

Platform & Ecosystem Integration:

- Microsoft AI Platform & Azure AI Services

- Copilot & Microsoft Fabric (Semantic models, notebooks, pipelines)

- Google AI Platform / Vertex AI

- Dataiku for collaborative data science and MLOps

- Ensure solutions follow enterprise architecture, security, and governance standards.

MLOps & Production Readiness:

- Build scalable, reliable, and observable ML pipelines including training, validation, deployment, and monitoring.

- Implement model versioning, performance tracking, drift detection, and retraining strategies.

- Collaborate with platform, cloud, and DevOps teams for seamless production deployments.

Required Skills & Qualifications:

Core Expertise:

- 7 - 10 years of experience in Data Science, Machine Learning, or Applied AI.

- Strong foundation in Statistics & Applied Mathematics (probability, regression, optimization, time series, etc.).

- Deep hands-on knowledge of Machine Learning algorithms and frameworks.

- Programming & Engineering

- Expert-level proficiency in Python.

Strong coding skills for:

- Machine learning & deep learning

- AI agent frameworks

- Data processing and orchestration

- Experience with modern ML/AI libraries (e.g., PyTorch, TensorFlow, scikit-learn, LangChain/agentic frameworks).

LLMs & Generative AI:

- Hands-on experience working with LLMs (prompt engineering, fine-tuning, RAG, evaluation).

- Experience deploying and managing LLM solutions across multiple AI platforms.

AI Agents & Protocols:

- Practical experience building AI Agents using:

1. Agent-to-Agent (A2A) architectures

2. Model Context Protocol (MCP) or similar standards

3. Strong understanding of tool calling, memory, planning, and reasoning patterns.

Platform & Domain Knowledge:

- Experience with Microsoft AI, Google AI Platform, and/or Dataiku.