Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The Staff Product Manager will drive pricing strategies and build tools for pricing performance, collaborating with teams to support brand success and growth.

Lead Finance Systems & Data, driving modernization and AI adoption in finance. Manage architecture, oversee data integrity, and develop a high-performing team.

Build and maintain revenue operations systems, reporting, forecasting, and compensation processes. Deliver analytical frameworks, pipeline diagnostics, ad hoc deep dives, and AI-driven automation to improve sales performance and decision-making while partnering cross-functionally.

The Fraud Strategy Lead will manage strategic fraud initiatives, partner with teams to enhance fraud tools, and mentor junior members, all while advancing fraud capabilities aligned with company objectives.

The Marketing Analytics Senior Lead will manage the analytics strategy for Lifecycle & CRM marketing, influence investment decisions, lead experimentation, and provide insights to enhance marketing efficiency across a global platform.

Provide executive-level support to five Brand leaders across time zones: manage complex calendars, run team operating rhythms, take meeting notes and track deliverables, plan onsites and events, prepare leaders for meetings, act as liaison with stakeholders, and use tools (G-Suite, Slack, AI) to drive efficiency while maintaining confidentiality and prioritizing shifting demands.

Lead the Discovery Experience team to create intuitive and personalized product discovery solutions for retailers, focusing on search UX and AI integration.

Serve as portfolio-level finance partner for International and Retailer Growth, building forecasting, telemetry, and frameworks to identify high-conviction growth investments. Drive topline growth forecasts, communicate performance to leadership, partner cross-functionally, and surface structural risks and opportunities to guide capital allocation decisions.

Lead Faire's experimentation methodology and operating system, design and review high-stakes experiments, provide causal-inference alternatives when A/B tests aren't possible, troubleshoot anomalous results, and partner with engineering, data science, and product to improve experiment infrastructure and metrics.

Lead and scale the Ads Data team, owning data and ML strategy across retrieval/ranking, bidding/auction systems, and data engineering. Hire and mentor applied scientists and analytics/engineers, set technical roadmap and operating model, partner cross-functionally, contribute hands-on to high-priority ML problems, and represent Ads Data in company strategy.