Engineering Manager, Rider Growth
- Recruit, mentor, and grow a diverse, inclusive, and highly skilled engineering team. Foster a culture of high ownership, rapid iteration, and technical craftsmanship.
- Partner with Product Management, User Experience (UX) Design, and Data Science, define the strategy and execute a roadmap aimed at accelerating rider growth and retention.
- Lead the technical strategy for rider onboarding, focusing on shrinking the time-to-value (TTV) from app download to the first driverless trip. Build smooth UX flows that solve high cognitive trust barriers, educate riders on vehicle safety, and optimize physical pickup/drop-off logistics.
- Architect and scale rider retention frameworks, including subscription services, commuter packages, and loyalty programs that incentivize frequent, habitual riding.
- Collaborate with ML scientists and economists to design and scale highly reliable, low-latency promotional engines. Build backend systems that distribute personalized, budget-capped promotions to shape rider demand and maximize incremental ridership.
- Champion a highly quantitative, data-driven engineering culture. Drive standard-setting experimentation practices, ensuring the team runs robust A/B tests, interprets statistical outcomes accurately, and rapidly integrates learnings back into the product.
- Oversee the scalability, latency, and reliability of your team's services. Ensure seamless, high-performance integrations with Waymo's core routing, fleet dispatch, pricing engines, and billing ledgers.
- 4+ years of experience directly managing and scaling high-performing software engineering teams, with a strong track record of mentoring senior and staff-level engineers.
- 6+ years of hands-on software development experience building highly scalable, distributed backend systems (Go, Java, C++, or Python) and/or high-performance B2C mobile applications (iOS/Android).
- Deep, practical experience running systematic product experiments (A/B testing, multivariate testing) with a strong grasp of statistical significance, experimental design, and cohort analysis.
- Fluency in using data analytics tools (SQL, Python/Pandas, Tableau, etc.) to diagnose user drops, analyze funnel health, and identify new conversion opportunities.
- The ability to thrive in a fast-paced, evolving environment, managing multiple parallel product experiments while maintaining absolute engineering craftsmanship.
- Extensive experience scaling B2C products by driving measurable improvements across the Acquisition, Retention, and LTV (Lifetime Value) lifecycle.
- Proven success architecting ML-driven systems for real-time offer surfacing and ranking, leveraging techniques like Multi-Armed Bandits to optimize incentives at scale.
- Outstanding communication and collaboration skills. You can seamlessly translate high-level business and economic goals into rigorous technical requirements and align stakeholders across the business.
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