Staff Data Scientist – ML, Gen AI & Agentic AI

About the role

The Staff Data Scientist is a senior individual contributor serving as a technical lead across Machine Learning, Generative AI, and Agentic AI initiatives. The role designs, develops, and scales advanced models, RAG-powered GenAI systems, and agentic workflows that power analytics across CPG growth, demand forecasting, pricing, supply chain, and manufacturing.

Responsibilities

• Design, build, and scale ML models for demand forecasting, growth analytics, price/pack elasticity, segmentation, trade promotion analysis, and supply-chain optimization.
• Develop end-to-end ML pipelines with strong feature engineering, validation, deployment, and model monitoring/observability.
• Deliver interpretable, production-ready models embedded into analytics products and decision experiences.
• Build RAG-powered GenAI solutions with retrieval design, prompting strategies, grounding, and evaluation frameworks.
• Develop tool-using and orchestrated agentic workflows to accelerate analytics and automate decision support.
• Partner with APM&I/product management and business leaders to translate prioritized use cases into measurable outcomes; DS owns the analytic/agent approach and validates performance; APM&I owns value framing and business sign-off.
• Communicate complex ML/GenAI concepts clearly to technical and business stakeholders, including model behavior, risks, and trade-offs.
• Implement Responsible AI practices covering safety, bias mitigation, privacy, evaluation, and telemetry.
• Provide technical leadership and mentorship without direct reports, guiding best practices, reviewing code/approaches, and elevating team capability.
• Contribute to enterprise AI governance, including model/agent documentation, risk assessments, access control, versioning, testing standards, and audit readiness.
• Foster cross-functional collaboration, identifying opportunities to leverage GenAI across manufacturing, supply chain, commercial operations, HR, legal, and corporate functions.

Qualifications

• Minimum Qualifications: 8+ years in Data Science/ML. Experience in CPG/retail growth, demand forecasting, pricing, and promotional analytics. Proficiency in Python, SQL, Snowflake, Azure ML/Databricks. Practical experience with ML techniques and emerging GenAI/LLM workflows. Strong communication and stakeholder alignment skills.
• Preferred Qualifications: 10–12+ years analytics experience. Experience with agent frameworks, vector databases, hybrid search. Experience operationalizing ML/LLM systems with CI/CD and observability. Familiarity with Power BI and analytics experience design.