Data & AI Consulting Manager / Senior Manager in Consumer & Retail

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• Deep expertise in Consumer & Retail industry or sustained consulting experience with retailers, CPG/FMCG, eCommerce, or wholesale.
• Consulting skills including structured problem-solving, stakeholder management, workshop facilitation, and executive communication.
• Data and AI literacy with ability to define data requirements and KPIs and communicate between business and technical audiences.
• End-to-end agile delivery experience from problem framing to delivery and adoption.
• Fluent in CPG data landscape including syndicated and panel data (e.g., NIQ/Nielsen, Circana, Kantar), retailer POS and portal feeds, distributor sell-out.
• Comfortable working with ambiguity and taking ownership to drive outcomes.

• Shape pursuits and proposals by contributing to presales activities including problem definition and scoping.
• Lead client discovery workshops with commercial, category, and supply chain leadership to identify real problems and define outcomes.
• Build business cases by prioritizing data and AI use cases, defining KPIs, investment rationale, and delivery roadmaps.
• Own the workstream end-to-end covering requirements, backlog management, data readiness, governance, and value tracking.
• Collaborate closely with Data Engineers, Data Scientists, and Solution Architects to design scalable solutions.
• Produce executive-level materials and present recommendations to leadership throughout engagements.
• Specific use cases include elasticity modelling, trade spend optimisation, assortment optimisation, customer segmentation, demand forecasting, and GenAI-enabled use cases such as commercial copilots and automation of analysis.

Nice to have:

• Familiarity with data cloud platforms like Databricks, Snowflake and hyperscalers such as Azure, GCP, or AWS.
• Experience with advanced analytics or GenAI patterns including forecasting, recommendation engines, optimisation, LLMs, and RAG.
• Hands-on exposure to hierarchical and time-series forecasting, econometric models, and causal inference.
• Knowledge of enterprise platforms such as SAP, Salesforce, major ERP, and CRM systems.
• Skills in change management and adoption.
• Experience in data governance and quality frameworks.
• Multi-market experience working across regional or global CPG models.

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