Lead Data Scientist

Job Title:

About the Role

Lead Data Scientist

Practice Head – Data Science and AI

Key Responsibilities

• Blueprint & Architecture:

  Translate business needs into logical workflows, data flows, and scalable technical architectures.

• Solution Delivery:

  Build and deploy advanced ML and GenAI solutions, including:
• Generative AI (document intelligence, semantic search, summarization, conversational Q&A).
  
• ML use cases (forecasting, classification, clustering, recommendation engines, anomaly detection).
  
• Model explainability, accuracy, and traceability.
  

• Deployment & Operations:

  Implement

  MLOps/GenAIOps

  practices, including CI/CD, monitoring, retraining, and governance frameworks.

• Cost & Ownership:

  Prepare

  Bills of Materials

  , infrastructure sizing, and

  total cost of ownership

  models for both client and internal deployments.

• Team Leadership:

  Mentor, coach, and manage a team of data scientists and engineers to deliver production-ready solutions.

• Stakeholder Engagement:

  Clearly communicate technical solutions, align deliverables with business priorities, and drive client adoption.

What We Expect

• Experience:

  8 - 12 years in Data Science/AI, with at least 3–4 years leading ML/GenAI solution delivery.

• Technical Skills:

• Strong expertise in

  Python

  , ML/AI frameworks, and LLM-based architectures.
• Hands-on experience with

  cloud platforms (AWS, Azure, GCP)

  .
• Familiarity with

  vector databases, RAG pipelines

  , and scalable data architectures.

• Business & Analytics:

  Solid foundation in BI tools, hypothesis testing, actionable insights, and making business-driven recommendations.

• Delivery Track Record:

  Proven history of taking solutions from

  design deployment adoption

  .

• Cost Estimation:

  Experience in infrastructure requirement analysis and ownership cost modeling.

• Education:

  Degree in Statistics, Mathematics, Economics, Computer Science, AI/ML, Data Science, or an equivalent quantitative discipline.

• Leadership & Soft Skills:

  Ambitious yet pragmatic leader with strong problem-solving, communication, and stakeholder management abilities.