Data & AI Consulting Manager / Senior Manager in Consumer & Retail - German Market

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

• Deep Consumer & Retail expertise with measurable business impact examples
• Consulting experience: structured problem-solving, stakeholder management, workshop facilitation, executive-level communication
• Data and AI literate: define data requirements and KPIs, translate between business and technical audiences
• End-to-end agile delivery experience from problem framing to adoption
• Fluent in CPG data landscape and practical experience with transaction, product, customer, syndicated, panel, POS and distributor data
• Comfortable with ambiguity and taking ownership
• Fluent in German or capable of client engagement in German is a strong plus

Nice to have:

• Familiarity with major data cloud platforms (Databricks, Snowflake) and hyperscalers (Azure, GCP, AWS)
• Experience with advanced analytics or GenAI patterns (forecasting, recommendation engines, optimization, LLMs, RAG) in Consumer & Retail
• Hands-on exposure to modeling families: hierarchical/time-series forecasting, econometric/elasticity models, optimization, causal inference, incrementality testing
• Knowledge of enterprise platforms like SAP, Salesforce or major ERP/CRM systems
• Change management and adoption skills
• Experience in data governance, data quality frameworks or operating model design
• Multi-market experience with regional/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 good outcomes
• Build the business case: identify, prioritize and size data and AI use cases; translate into business cases with KPIs, investment rationale and delivery roadmaps
• Own the workstream end-to-end: requirements, backlog, data readiness, governance and value tracking through to adoption
• Brief builders: work closely with Data Engineers, Data Scientists and Solution Architects to design scalable solutions
• Produce clear, executive-level materials and present recommendations to leadership
• Conduct pricing & promotions analytics: elasticity modeling, promotional effectiveness, trade spend optimization, net revenue management
• Conduct merchandising & category analytics: assortment optimization, product performance, markdown and clearance
• Customer & growth analytics: segmentation, CLV, churn/retention, personalization, next-best-action
• Demand & supply chain analytics: demand forecasting and sensing, replenishment, availability and fulfillment analytics
• Develop GenAI-enabled use cases: commercial copilots, knowledge and insight agents, automation of analysis and reporting

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