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

EPAM Systems is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. They have over thirty years of expertise in custom software, product and platform engineering. The role is within the Consumer & Retail practice, focusing on AI and advanced analytics initiatives.

• Deep Consumer & Retail expertise with measurable business impact in industry or consulting (retailers, CPG/FMCG, eCommerce, wholesale)
• Consulting experience including structured problem-solving, stakeholder management, workshop facilitation, and executive communication
• Data and AI literacy to define requirements, communicate with data scientists/architects, and translate between business and technical teams
• End-to-end agile delivery experience from problem framing to adoption
• Familiarity with CPG data landscape including syndicated/panel data (NIQ/Nielsen, Circana, Kantar), retailer POS and distributor data
• Ability to work with ambiguity, take ownership, and drive outcomes independently

Nice to have:

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

• Contribute to presales by defining problems, scoping approaches, and building value narratives for Consumer & Retail clients
• Facilitate client discovery workshops with commercial, category, and supply chain leadership to define real problems and outcomes
• Build business cases by identifying, prioritizing, and sizing data and AI use cases with KPIs, investment rationale, and delivery roadmaps
• Own workstreams end-to-end including requirements, backlog management, data readiness, governance, and value tracking through adoption
• Collaborate closely with Data Engineers, Data Scientists, and Solution Architects to design scalable solutions
• Produce executive-level materials and present recommendations to leadership
• Address pricing & promotions through elasticity modelling, promotional effectiveness, trade spend optimization, and net revenue management
• Support merchandising & category analytics like assortment optimisation, product performance, markdown, and clearance
• Work on customer & growth analytics including segmentation, CLV, churn/retention, personalisation, and next-best-action
• Manage demand & supply chain analytics such as demand forecasting, replenishment, availability, and fulfilment
• Lead GenAI-enabled use cases like commercial copilots, knowledge and insight agents, and automation of analysis and reporting

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