Top Remote Data & Analytics Jobs in San Francisco Bay Area, CA

The Fraud Risk Analytics Manager will lead fraud risk strategy optimization and provide analytical insights to reduce fraud risk and enhance customer outcomes. They will partner with teams to ensure transparency and governance in fraud strategies, using advanced data analysis techniques to drive decision making.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Client Analyst will manage client-facing data and analytics requests, align objectives with campaign performance, provide insights, and optimize campaigns for key accounts.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

As a Lead Analyst, you'll optimize trading performance by assessing exchanges, building analytical frameworks, partnering with traders, and developing dashboards.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

The Vehicle Data Editor will manage automotive data entry, ensuring completeness and accuracy by researching and interpreting data from OEMs and assisting in data cleanup projects.

The role involves analyzing insurance classification frameworks, creating mapping documentation, and communicating classification rationale while working with stakeholders.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.