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

The role involves analyzing complex pricing strategies, conducting data-driven analyses, collaborating with cross-functional teams, and translating insights into strategic business recommendations.

Seeking backend engineers to build and maintain APIs for payment processing, collaborating with cross-functional teams and mentoring peers.

Design, build, and maintain backend systems and versioned APIs for payments; collaborate with product, design, and infra; deliver features, tests, deployments, and long-term roadmaps while upholding high engineering standards.

The Product Designer will oversee the design of internal tools, collaborate with engineers and PMs, and ensure usability while contributing to design consistency and quality across the internal tools suite.

Provide financial insights and pricing support for sales teams by developing frameworks for pricing strategies and collaborating with cross-functional partners to enhance deal attractiveness.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

The role involves writing and maintaining fraud rulesets, conducting data analysis to identify and mitigate fraud, and collaborating with cross-functional teams to implement fraud strategies.

As a Payments Fraud Investigator, you will analyze high-risk accounts, lead investigations into fraud incidents, and collaborate on cross-functional projects to enhance fraud detection and prevention strategies.

Lead and execute large, global regulatory programs end-to-end. Design and scale cross-functional PMO operating models, track deliverables, manage change, translate regulatory requirements into commercial strategy, drive process improvements, advise senior stakeholders, gather user feedback, and build scalable systems to prevent operational gaps.

Analyze operational performance for Tax operations by conducting deep-dive investigations, identifying root causes, building dashboards and self-serve reporting, applying statistical methods to evaluate experiments, and communicating actionable insights to operations and leadership to improve measurement and scalability.