Job Description :

We are looking for a Lead Data Scientist to head the Data Science / AI team and to design, build, and deploy repeatable data and machine-learning pipelines and AI solutions. You will lead the Data Science / AI team of 5 to 6 data scientists and AI engineers plus several interns while staying hands-on as a senior individual contributor.

You will own the Data Science / AI roadmap and its delivery across EnMS & BESS energy analytics, the Aetrium Assistant (Conversational AI) and agentic workflows. You will be involved in the end-to-end delivery of systems, including exploring, understanding and processing data, designing and building pipelines, understanding model outputs and evaluating performance against defined objectives, and communicating these results.

Role Summary :

You will also need to communicate complex technical ideas to varied audiences. You will be involved in customer interactions needed to design and deploy the solutions.

You must have the ability to understand deployability of solutions across various Industry Verticals such as Energy, Manufacturing, BFSI etc. You will hire, coach and set the technical bar for the team, and be accountable for its delivery, quality and growth.

Key Result Areas :

- End-to-End ML pipeline Development: Design, train, tune, test, and deploy robust, repeatable ML model pipelines.

- Data Analysis: Perform data analysis on large datasets, design features, accommodate data quality issues and identify patterns for solutions.

- Production Deployment: Understand, advise and configure infrastructure for pipeline execution within cloud environments.

- Roadmap Ownership: Own and drive the technical & AI development roadmap, priorities and direction.

- Customer Collaboration.

- Team Leadership & Mentorship: Build, coach and grow a team of 5 to 6 data scientists / AI engineers and interns.

- Hiring & Capability Building: Recruit and develop talent; set standards and ways of working.

- Energy AI: EnMS & BESS analytics - monitoring, optimization, forecasting and degradation-aware models.

- Delivery Accountability: Team-level delivery, quality, reliability and production outcomes.

- Sprint Management.

- Code Management.

- LLM Application Development, LLM Orchestration & Optimization.

- Agentic AI & Workflow Integration.

- RAG (Retrieval-Augmented Generation).

- Multilingual & NLP capabilities / NLP to SQL capabilities for assistants.

Technical Requirements:

- Developing Machine Learning pipelines and MLOps.

- Data analysis, data exploration, and identifying patterns.

- Delivering software into large enterprise environments.

- Developing or deploying models, feature engineering, model evaluation and iteration.

- Understanding of statistics.

- Working as a part of a team with version control technologies.

- Leading and mentoring a team - sprint planning, code review and delivery ownership.

- Client-facing skills, or equivalent demonstration of stakeholder management.

- Design evaluation frameworks for accuracy, relevance, and safety.

Must have skills :

- Experience using Git for code versioning.

- Experience using Jira to create Sprints.

- Proven experience leading and mentoring a data science / ML team.

- Experience owning delivery roadmaps, sprint planning and stakeholder management.

- Experience using MLOps, such as DVC, MLflow, etc for model tracking.

- Knowledge of statistical concepts.

- Strong experience with LLMs (e.g., Open AI, open-source models).

- Hands-on with LangChain / LangGraph / LlamaIndex (or similar).

- Proficiency in Python (mandatory).

- Proficiency in Pytorch (mandatory).

- Proficiency in SQL (mandatory).

- Understanding of NLP concepts (tokenization, embeddings, transformers).

- Understanding of Computer Vision concepts.

- Experience with HuggingFace ecosystem.

- Vector Databases (FAISS, Pinecone, Weaviate).

- Experience building scalable, production-grade AI systems.

- Knowledge of APIs, microservices.

- Knowledge of Async processing.

- Experience with Voice AI (STT / TTS integration).

- Experience with Real-time AI systems.

Desired Skills :

- Exposure to Multilingual AI (Indic languages).

- Experience in the energy / industrial domain (EnMS, BESS, Industry 4.0).

- Familiarity with Agent Frameworks (MCP, CrewAI, AutoGen, etc).

- Claude certification.

- Experience working with large datasets using Spark, Airflow, etc.