We are seeking a Data & AI Consultant to join our team and help clients across CPG, retail, restaurants and QSR, travel and hospitality turn data into business outcomes. In this role, you will combine strong data and analytics solution design capability with deep knowledge of pricing, promotion, merchandising, and trade spend to define the strategies and architectures that power revenue growth management decisions. Req.#[redacted] Responsibilities Partner with clients to understand business objectives, challenges, and data requirements across pricing, promotion, assortment, and trade spend, and translate them into data and analytics solution designs Define data and AI strategies and roadmaps for revenue growth management, merchandising, and trade promotion analytics Design analytics solution architectures spanning POS/scanner, syndicated panel, loyalty, and trade data from providers such as NielsenIQ, Circana, etc. Define modeling approaches for price elasticity, promotion lift and ROI, demand forecasting, and assortment optimization, and guide data science teams through implementation Analyze CPG, consumer, market, and sales data to synthesize findings into clear, actionable insights and recommendations Shape analytics solution designs that make pricing, promotion, and merchandising insights usable by client teams Identify opportunities to apply advanced analytics and AI/ML to accelerate insight generation on commercial data Create and deliver clear technical and business presentations that communicate complex analytical results and recommended solutions Collaborate with data engineers, data scientists, and client commercial teams to guide delivery of end-to-end analytics solutions Requirements Strong experience in data and analytics consulting with the ability to design solutions and guide technical teams (working knowledge of SQL and Python or R) In-depth understanding of commercial functions (pricing, promotion, merchandising, trade terms) in at least one consumer industry, with the ability to extend that expertise across adjacent sectors Proven ability to define data and analytics solution architectures and translate business problems into technical approaches Experience with syndicated data providers (NielsenIQ, Circana, Numerator, dunnhumby, 84.51°, SPINS) and/or RGM or trade promotion platforms (Vistex, o9, Blue Yonder, Revionics, PROS) highly desirable Experience applying AI to commercial analytics use cases Familiarity with cloud data platforms (Databricks, Snowflake, AWS, Azure, or GCP) Strong communication and stakeholder management skills, able to translate technical analysis and strategy for business audiences Nice to have Exposure to marketing mix modeling or causal inference/elasticity modeling