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

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.

Lead end-to-end performance creative strategy: write production-ready briefs, develop and maintain a backlog of concepts, analyze performance data to inform creative playbooks, manage UGC creator pipeline and relationships, and drive cross-vertical testing and iteration across formats.

Lead BI developer owning end-to-end reporting for performance marketing verticals. Build and standardize dashboards, author LookML models, extract insights from messy third-party data, partner with Yield/Paid Media/Account teams, deliver retrospective analyses, and drive adoption and business impact.

Lead BI Developer owns reporting infrastructure end-to-end, building standardized, trusted dashboards and LookML models, analyzing messy third-party data, partnering with Yield/Paid Media/Account teams to deliver actionable performance marketing insights and retrospective analyses that drive business decisions.

Lead creative strategy for performance-driven digital content: write production-ready briefs, develop and maintain concept backlogs and playbooks, analyze paid performance to inform creative, manage UGC creator pipeline end-to-end, and drive cross-vertical testing and iteration to maximize ad performance.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

Lead end-to-end applied ML for an adtech vertical (Insurance): frame business problems, build and validate models, partner with ML engineering for deployment, monitor live ROAS, and drive measurable lead quality and revenue improvements.

Own end-to-end data science for a priority vertical (starting with Insurance): frame business problems, build and validate models, partner with ML engineering for deployment, monitor live ROAS performance, and drive measurable revenue and lead quality improvements.

Lead end-to-end applied data science for a priority vertical (starting with Insurance), from problem framing to deployed models and live ROAS performance. Build, validate, monitor, and iterate ML models for paid media, ad ranking, recommendation, LTV and funnel optimization, partnering with ML engineering and business stakeholders to drive measurable revenue and lead quality improvements.