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

EPAM is a 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, EPAM empowers clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• Deep Consumer & Retail expertise with measurable business impact from industry or consulting experience involving retailers, CPG/FMCG, eCommerce, or wholesale clients
• Consulting experience including structured problem-solving, stakeholder management, workshop facilitation, and executive-level communication
• Data and AI literate: capable of defining data requirements and KPIs, conversing with data scientists and architects, translating between business and technical audiences
• End-to-end agile delivery experience: from problem framing and business case through to delivery and adoption
• Familiarity with CPG data landscape: syndicated and panel data (e.g., NIQ/Nielsen, Circana, Kantar), retailer POS and portal feeds, distributor sell-out
• Comfortable with ambiguity, takes ownership and drives towards outcomes independently

Nice to have:

• Familiarity with major data cloud platforms (Databricks, Snowflake) and hyperscalers (Azure, GCP, AWS)
• Experience with advanced analytics or GenAI patterns including forecasting, recommendation engines, optimisation, LLMs, RAG in Consumer & Retail context
• Hands-on exposure to hierarchical and time-series forecasting, econometric and elasticity models, optimisation, causal inference, incrementality testing
• Knowledge of enterprise platforms such as SAP, Salesforce, or major ERP and CRM systems
• Change management and adoption skills for solution implementation
• Experience in data governance, data quality frameworks, or target operating model design
• Multi-market experience across regional or global CPG operating models

• Shape pursuits and proposals: contribute to presales from the start, defining the problem, scoping the approach, and building EPAM’s value narrative for Consumer & Retail clients
• Lead client discovery: facilitate workshops with commercial, category and supply chain leadership, frame the real problem, and define what a good outcome looks like
• Build the business case: identify, prioritise and size data and AI use cases; translate them into business cases with KPIs, investment rationale and delivery roadmaps that get sign-off
• Own the workstream end-to-end: requirements, backlog, data readiness, governance and value tracking through to adoption
• Brief the builders: work closely with Data Engineers, Data Scientists and Solution Architects to design scalable solutions
• Produce executive-level materials and present recommendations to leadership throughout engagements
• Apply pricing & promotions analytics: elasticity modelling, promotional effectiveness, trade spend optimisation, net revenue management
• Manage merchandising & category analytics: assortment optimisation, product performance, markdown and clearance
• Handle customer & growth analytics: segmentation, CLV, churn/retention, personalisation, next-best-action
• Manage demand & supply chain analytics: demand forecasting and sensing, replenishment, availability and fulfilment analytics
• Develop GenAI-enabled use cases: commercial copilots, knowledge and insight agents, automation of analysis and reporting

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