Director, SME AI & Pricing (Car Rental / Mobility)
Fetcherr, Miami, FL, United States
Subject Matter Expert (Sme) For Ai-driven Pricing Solution
Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Initially focused on the airline industry, Fetcherr is expanding to transform additional verticals with dynamic AI-driven solutions. We are looking for a subject matter expert (SME) to support the development of a new AI-driven pricing solution tailored to the car rental and mobility industry. The ideal candidate brings hands-on experience in fleet-based pricing, rental demand modeling, or revenue optimization within car rental, OTA, or mobility platforms. This role will act as a strategic advisor to our product, data, and engineering teams helping shape the solution, validate assumptions, and guide the development of models and data strategy specific to the car rental environment (e.g., utilization-driven pricing, seasonality, station-level demand, length-of-rental dynamics, ancillary/VAS upsell). Key responsibilities: Advise on AI/ML approaches for rental pricing optimization, demand prediction, and fleet utilization Help define data requirements specific to car rental operations: reservation data, check-in/check-out patterns, competitor rate feeds, channel mix, and fleet availability Provide deep expertise on car rental pricing dynamics including rate categories, length-of-rental (LOR) pricing, advance purchase behavior, walk-up rates, and blackout periods Guide revenue management strategy covering occupancy vs. yield trade-offs, overbooking logic, and dynamic rate adjustment Advise on VAS (value-added services) pricing: insurance products, GPS, fuel options, upgrades, and bundling strategies Work closely with product, data, and engineering teams to translate business logic into model features and product requirements Validate model assumptions, review outputs against real-world rental scenarios, and help prioritize experiments Share knowledge on industry benchmarks, competitive pricing behavior, and channel-specific pricing strategies (direct, OTA, corporate, broker) Requirements: Proven experience in pricing optimization, demand forecasting, or revenue management specifically within car rental, vehicle leasing, or mobility - a must Familiarity with car rental systems and data sources (e.g., ACRISS codes, RMS platforms, GDS/OTA connectivity, reservation systems such as Rentalmatic, Bluebird, or similar) Ability to bridge business knowledge and data/product teams translating rental market logic into actionable modeling strategies Experience working in an advisory or consulting capacity, comfortable with fast-moving, agile product environments Knowledge of key industry metrics: fleet utilization, RevPAC (Revenue per Available Car), EBIT contribution of VAS, channel margin profiles Able to work hybrid (2-3 times a week from office) at 175 SW 7 ST Suite 1900, Miami, FL 33130.
Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Initially focused on the airline industry, Fetcherr is expanding to transform additional verticals with dynamic AI-driven solutions. We are looking for a subject matter expert (SME) to support the development of a new AI-driven pricing solution tailored to the car rental and mobility industry. The ideal candidate brings hands-on experience in fleet-based pricing, rental demand modeling, or revenue optimization within car rental, OTA, or mobility platforms. This role will act as a strategic advisor to our product, data, and engineering teams helping shape the solution, validate assumptions, and guide the development of models and data strategy specific to the car rental environment (e.g., utilization-driven pricing, seasonality, station-level demand, length-of-rental dynamics, ancillary/VAS upsell). Key responsibilities: Advise on AI/ML approaches for rental pricing optimization, demand prediction, and fleet utilization Help define data requirements specific to car rental operations: reservation data, check-in/check-out patterns, competitor rate feeds, channel mix, and fleet availability Provide deep expertise on car rental pricing dynamics including rate categories, length-of-rental (LOR) pricing, advance purchase behavior, walk-up rates, and blackout periods Guide revenue management strategy covering occupancy vs. yield trade-offs, overbooking logic, and dynamic rate adjustment Advise on VAS (value-added services) pricing: insurance products, GPS, fuel options, upgrades, and bundling strategies Work closely with product, data, and engineering teams to translate business logic into model features and product requirements Validate model assumptions, review outputs against real-world rental scenarios, and help prioritize experiments Share knowledge on industry benchmarks, competitive pricing behavior, and channel-specific pricing strategies (direct, OTA, corporate, broker) Requirements: Proven experience in pricing optimization, demand forecasting, or revenue management specifically within car rental, vehicle leasing, or mobility - a must Familiarity with car rental systems and data sources (e.g., ACRISS codes, RMS platforms, GDS/OTA connectivity, reservation systems such as Rentalmatic, Bluebird, or similar) Ability to bridge business knowledge and data/product teams translating rental market logic into actionable modeling strategies Experience working in an advisory or consulting capacity, comfortable with fast-moving, agile product environments Knowledge of key industry metrics: fleet utilization, RevPAC (Revenue per Available Car), EBIT contribution of VAS, channel margin profiles Able to work hybrid (2-3 times a week from office) at 175 SW 7 ST Suite 1900, Miami, FL 33130.