Global Data Science Senior Manager – Chapter Lead

BCG BCG · Consulting · Gurgaon, Haryana, India · Data Science and Analytics

Senior Manager, Chapter Lead for Data Science at BCG, focusing on enterprise GenAI, LLMs, and Agents. This role requires significant hands-on individual contributor work in developing and deploying AI/ML solutions at scale, combined with leadership responsibilities for people management and senior stakeholder engagement. The position involves applying machine learning, statistical techniques, and NLP to solve complex business problems, translating business needs into scalable AI solution designs, and mentoring junior team members. Experience with RAG, LangChain, and cloud platforms is expected.

What you'd actually do

  1. Develop and deploy data science models using Python
  2. Apply machine learning and statistical techniques to solve business problems
  3. Work on use cases across predictive modeling, analytics, and NLP
  4. Translate business needs into scalable AI solution designs and delivery plans
  5. Collaborate with cross-functional teams to deliver data-driven solutions

Skills

Required

  • Python
  • GenAI
  • LLMs
  • Agents
  • Machine Learning
  • Statistical Techniques
  • NLP
  • Data Science
  • Prompt Engineering
  • RAG
  • LangChain
  • Cloud Platforms (AWS, GCP, Azure)
  • MLOps

Nice to have

  • Tableau
  • Power BI
  • Snowflake

What the JD emphasized

  • Strong technical depth is essential
  • Practical experience building and deploying AI/ML or GenAI and Agentic solutions at scale
  • hands-on experience in GenAI, LLMs, and Agents
  • Strong hands-on proficiency in Python for data science and problem solving
  • Solid foundation in machine learning and statistical techniques
  • Exposure to GenAI / LLM use cases (e.g., RAG, NLP applications)
  • Ability to translate business problems into data-driven solutions
  • Experience working with real-world datasets and deploying models in practice
  • Strong communication skills and ability to work with senior stakeholders
  • Leading and inspiring technical teams
  • Bridging strategy and execution
  • Applying deep technical expertise
  • Designing and scaling AI solutions
  • Designing for scalability and performance
  • Driving innovation and continuous improvement
  • Simplifying complexity
  • Collaborating across disciplines
  • Coaching and capability building
  • Operating with agility and structure

Other signals

  • hands-on experience in GenAI, LLMs, and Agents
  • enterprise-scale Data Science, AI, and Agent initiatives
  • building and deploying AI/ML or GenAI and Agentic solutions at scale
  • GenAI / LLM use cases (e.g., RAG, NLP applications)
  • large language models (LLMs), and generative AI frameworks (e.g., LangChain)
  • retrieval-augmented generation (RAG) techniques
  • designing and scaling AI solutions