Data & Al Consulting Manager (Consumer & Retail) (k/m)

The role is within the Consumer & Retail practice at EPAM, focusing on translating real business problems into actionable AI and data solutions in the commercial and retail sectors.

• Deep Consumer & Retail expertise from industry or sustained consulting with retailers, CPG/FMCG, eCommerce, or wholesale clients with measurable business impact
• Consulting experience including structured problem-solving, stakeholder management, workshop facilitation, and executive-level communication
• Data and AI literacy: ability to define data requirements and KPIs, communicate with data scientists or architects, and translate between business and technical audiences
• End-to-end agile delivery experience from problem framing to delivery and adoption, with insight into what worked and what did not
• Fluent in the CPG data landscape including transaction/order, product, customer data (CRM, loyalty), syndicated and panel data (NIQ/Nielsen, Circana, Kantar), retailer POS and portal feeds, distributor sell-out, and practical use
• Comfortable with ambiguity by taking ownership and driving outcomes without explicit directions

• Shape pursuits and proposals: contribute to presales from the start by defining problems, scoping approaches, and building EPAM's value narrative for Consumer & Retail clients
• Lead client discovery: facilitate workshops with leadership to frame real problems and define good outcomes
• Build the business case: identify, prioritize, and size data and AI use cases; translate into business cases with KPIs and delivery roadmaps
• Own the workstream end-to-end including requirements, backlog, data readiness, governance, and value tracking through adoption
• Collaborate with Data Engineers, Data Scientists, and Solution Architects to design scalable solutions by defining the what and why
• Produce clear executive-level materials and present recommendations to leadership throughout engagements
• Address pricing & promotions through elasticity modeling, promotional effectiveness, trade spend optimization, and net revenue management
• Work on merchandising & category topics like assortment optimization, product performance, markdown, and clearance
• Engage in customer & growth analytics including segmentation, CLV, churn/retention, personalization, next-best-action
• Handle demand & supply chain analytics such as demand forecasting, replenishment, availability, and fulfillment analytics
• Develop GenAI-enabled use cases like commercial copilots, knowledge and insight agents, automation of analysis and reporting