Revenue Growth Management only works when Sales, Marketing and Commercial Excellence are pulling the same lever at the same time. Most Consumer & Retail organizations don't have one person who can sit across all three and turn pricing, promotion and mix into a strategy everyone actually commits to. You want to be that person for our clients: the subject matter expert and trusted partner Sales, Marketing and ComEx bring into the room when RGM strategy needs to be built, not just reported on. As a Data & AI Manager and RGM subject matter expert in our Consumer & Retail practice, you will be the key stakeholder client teams across Sales, Marketing and Commercial Excellence rely on to shape their Revenue Growth Management strategy. You won't run a delivery team — you will own the thinking and the relationship: framing the strategy, challenging assumptions, and briefing Data Engineers, Data Scientists and Solution Architects so what gets built actually holds up commercially. You won't be building the pricing models yourself, but you will need to be fluent enough in elasticity, trade spend and mix economics to shape a strategy, defend it across functions, and know when the data is telling a different story than the client expects. Typical problems you'll work on Pricing strategy & elasticity: price-pack architecture, elasticity modeling, competitive price positioning Promotion effectiveness: promo ROI, trade spend optimization, promotional calendar redesign Net Revenue Management: waterfall analysis, deduction and off-invoice discount management, mix optimization Assortment & mix: SKU rationalization, channel and customer mix, markdown and clearance strategy GenAI-enabled RGM: pricing copilots for category and revenue managers, scenario simulation agents, automation of margin analysis and reporting Responsibilities Be the client's RGM subject matter expert: build trusted, ongoing relationships with Sales, Marketing and Commercial Excellence stakeholders as the go-to expert on pricing, promotion and mix strategy Shape the strategy: facilitate discovery across Sales, Marketing and ComEx, and translate competing commercial priorities into one clear, prioritized RGM strategy Build the business case: size RGM opportunities, structure the investment case, and secure sign-off from client leadership on the roadmap and its sequencing Brief the builders: define requirements and commercial guardrails for Data Engineers, Data Scientists and Solution Architects, and hold the solution accountable to the strategy Own value tracking: make sure the strategy lands as adopted ways of working across Sales, Marketing and ComEx, not a one-off recommendation Grow the practice: contribute to RGM proposals and presales, and build EPAM's point of view on Revenue Growth Management Requirements Deep RGM expertise: hands-on experience shaping Revenue Growth Management strategy — pricing, promotion, trade spend or mix — built in-industry or through sustained consulting with CPG/FMCG, retail or wholesale clients, with concrete, quantified business impact Trusted partner across the commercial organization: a proven ability to build credibility and long-term relationships across Sales, Marketing and Commercial Excellence, not just one function Consulting craft: structured problem-solving, executive-level communication, and comfort building alignment across stakeholders with different priorities Data and AI literate: able to define data and modeling requirements, hold a substantive conversation with a data scientist or pricing analyst, and translate between commercial and technical audiences End-to-end experience: from strategy through to delivery and adoption, with a clear, honest view of what worked and what didn't Comfortable with ambiguity: takes ownership and drives a client to outcomes without waiting to be told what the answer is English proficiency at B2 level or higher Nice to have Familiarity with RGM/pricing platforms (e.g., Revionics, Pricefx, Blue Yonder, Impact Analytics, PROS) or major cloud platforms (Azure, GCP, AWS) Experience with advanced analytics or GenAI patterns applied to pricing and promotion (elasticity models, optimization, LLMs, RAG) Knowledge of enterprise platforms common in Consumer & Retail environments (SAP, Salesforce, TPM/TPO systems) Experience in data governance or target operating model design for commercial functions
