Director, Subject Matter Expert — Consumer Appliances Pricing & Retail Revenue Management

About Fetcherr

Fetcherr is an AI‑driven company specializing in deep learning, algorithmic trading, and large‑scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real‑time, data‑driven decision‑making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

• Advise on approaches for promotional pricing optimization, including pMAP (Promotional Advertised Price) recommendations, intra‑period audibles, and MAP strategy across retail channels.
• Help define data requirements specific to consumer appliances: historical SKU‑level sales data, promotional calendars, competitive rate feeds, channel mix (big‑box, DTC, marketplace), and regional demand signals.
• Provide deep expertise on appliance retail pricing dynamics including MSRP, MAP, and pMAP mechanics, promotional event cadence (typically 2–4 week cycles), advance planning timelines, and retailer negotiation practices.
• Guide revenue management strategy covering promotional lift measurement, seasonality adjustments, SKU‑level optimization trade‑offs, and the tension between volume and margin across retail and DTC channels.
• Advise on direct‑to‑consumer and marketplace pricing: where GE and similar manufacturers have direct price control and can operate at a faster optimization cadence than through big‑box retail.
• Work closely with product, data, and engineering teams to translate pricing business logic into model features and product requirements — including explainability requirements critical for adoption.
• Validate model assumptions, review recommendations against real‑world retail scenarios, help define guardrail frameworks, and prioritize experiments during the pilot phase.
• Conduct a structured gap analysis between Fetcherr’s current product capabilities and the requirements of the consumer appliances and retail pricing environment.
• Share knowledge on industry benchmarks, competitive pricing behavior, and channel‑specific dynamics (Home Depot, Lowe’s, Best Buy, OTA, GE direct), including how promotional compliance and retailer sell‑through interact.

• Proven experience in pricing optimization, demand forecasting, or revenue management — specifically within consumer appliances manufacturing, big‑box retail, or durable goods e‑commerce — a must.
• Deep familiarity with retail pricing mechanics: MSRP, MAP, and pMAP structures; promotional event planning and execution; retailer co‑op agreements; and intra‑period price adjustment processes (audibles).
• Ability to bridge business knowledge and data/product teams — translating retail pricing logic and promotional dynamics into actionable modeling strategies and feature definitions.
• Experience with relevant data sources and systems: POS/sell‑through data by SKU and region, competitive price monitoring tools, promotional planning systems, and channel performance reporting.
• Familiarity with key industry metrics: promotional lift, sell‑through rate, revenue per SKU, channel margin contribution, and the trade‑off between promotional depth and long‑term price integrity.
• Familiarity with the structural challenges manufacturers face in their pricing and supply relationships with retailers — including power dynamics around MAP enforcement, retailer margin expectations, promotional funding, and the tension between manufacturer pricing intent and retailer execution.
• Experience working in an advisory or consulting capacity, comfortable with fast‑moving, agile product environments and early‑stage pilots with significant ambiguity.
• Bonus: experience with AI‑driven pricing tools, revenue management platforms, or working alongside data science teams on pricing model validation and experimentation design.

Ability to work hybrid (2–3 times a week from office) in Kentucky.