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

Provide hands-on end-user IT support: troubleshoot OS/software, respond to tickets, apply patches, manage user accounts via Okta, configure MDM-managed mobile devices, and support Slack and Google Workspace integrations.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Lead and grow a multidisciplinary product design team while contributing hands-on to high-priority design work. Drive visual refresh and evolution of the design system, partner cross-functionally (Product, Engineering, Marketing, Growth, Compliance), and manage hiring, performance, succession planning, and professional development to deliver cohesive, scalable user experiences for a regulated crypto platform.

Join the engineering team as a Software Engineering Intern to build backend, frontend, or full-stack features using Java, Spring Boot, TypeScript, React, and AWS. Write clean, testable code, participate in code reviews and agile ceremonies, collaborate with DevOps/QA/Product, and help improve system reliability and developer productivity during a replatform effort.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Develop and deploy ML-based fraud and risk models to detect financial crime and reduce losses. Design A/B tests, create risk signals and monitoring metrics, build tools and dashboards, provide technical leadership, and perform ad-hoc analyses in collaboration with Risk, Compliance, Product, and Marketing teams.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.