Lead /Head - Data Science

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 pf 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. 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.
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

Job Description

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