About the role

Senior Staff Revenue Strategy and Yield Manager defining global revenue strategy for an autonomous fleet. Leading experimentation and optimization for maximizing economic value per vehicle and ride.

Responsibilities

Define and own the revenue, pricing, and yield strategy establishing the frameworks and long-range roadmap that maximize revenue per vehicle and per ride.
Design, test, and operationalize advanced pricing models—including dynamic pricing, willingness-to-pay segmentation, supply/demand balancing, and marketplace health metrics—to improve unit economics without compromising customer trust.
Develop differentiated product and service packages (e.g., tiers, bundles, B2B offerings) and partner with Go-to-Market teams to bring them to market with clear value propositions and measurable impact.
Translate insights into executive-level recommendations, influencing C-suite, Product, Engineering, Operations, and Finance stakeholders to drive monetization decisions.
Serve as the executive-level thought partner to Product & Engineering, ensuring the technical roadmap (pricing engines, ML models, experimentation capabilities, marketplace tools) unlocks revenue and yield optimization at scale.
Build and institutionalize global revenue processes and playbooks, enabling consistent experimentation, forecasting, and pricing governance across markets.
Monitor marketplace dynamics, external benchmarks, and competitive signals to proactively identify pricing risks, opportunities, and required strategy shifts

12+ years of experience in pricing strategy, revenue management, marketplace economics, growth strategy, or related analytical roles; experience in autonomous vehicles, mobility, travel, tech marketplaces, or logistics preferred.
Deep expertise in dynamic pricing, yield management, and marketplace economics, with a strong track record of designing and scaling monetization models in complex, multi-sided platforms.
Advanced analytical and modeling skills, including experimentation design (A/B, quasi-experimental methods), causal inference, segmentation, and forecasting.
Proficiency with analytical tools such as SQL, Python/R, and BI platforms; ability to independently pull data, build models, and validate insights.
Demonstrated ability to influence executive stakeholders and drive cross-functional decisions through clear storytelling, robust financial modeling, and data-backed recommendations.
Experience partnering closely with Product and Engineering on pricing systems, ML-based optimization models, experimentation platforms, and/or marketplace tooling.
Excellent communication and narrative-building skills, with the ability to simplify complex economic concepts for diverse audiences.
Bias toward action and experimentation, with a track record of building new strategies, frameworks, or monetization programs from zero-to-one.
Bachelor’s degree required in Economics, Engineering, Mathematics, Business, or a related field; MBA or advanced quantitative degree preferred.