Lead Data Scientist

What You'll Bring

• 6-10 years in Data Science/ML roles, with meaningful experience in enterprise SaaS and/or CPG/Retail forecasting or Revenue Growth Management.
• At least one complete AI/ML product development lifecycle from early build through to a scaled, customer-facing product — not just research or POC work.
• Direct experience with demand forecasting, price elasticity, or related time-series/causal modelling problems at production scale.
• Strong Python ecosystem fluency: Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, Prophet or equivalent.
• Comfort with cloud platforms (Azure/GCP) and building distributed, production-grade pipelines.
• Demonstrated ability to work directly with customers or business stakeholders, translating ambiguous problems into technical scope.
• Bachelor's/Master's/PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field.

Nice to Have

• Experience in AI/tech consulting engagements for CPG or retail clients.
• Exposure to GenAI/LLM-based applications and AI agents.
• Experience with MLOps tooling, orchestration systems, and real-time inference pipelines.
• Patents, published research, or hackathon/competition track record.
  

Desired Candidate Profile

• 6-10 years of experience as a Data Scientist or related field with expertise in statistics, machine learning, artificial intelligence.
  
• Strong proficiency in programming languages such as Python; experience with R is an added advantage.
  
• Bachelor's degree in Engineering (B.Tech / B.E.) or equivalent specialization; Master's degree preferred.