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

The Cloud FinOps Practitioner will design and implement cloud financial operations, focusing on cost optimization, governance, and collaboration across teams to enhance efficient cloud usage.

As a Staff Analytics Engineer, you'll lead analytics architecture, ensure data quality, collaborate with stakeholders, and drive AI-powered data insights for business decision-making.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

Lead architect for Compliance data at Coinbase, defining data governance frameworks, designing data contracts, mapping data lineage, and quantifying data impact to enhance compliance reporting and data quality processes.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead analytics strategy for a financial institution, ensuring compliance and driving marketing analytics through predictive modeling and team management.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

The Data Scientist will build analytics infrastructure, conduct analysis and modeling, and collaborate with teams to enhance data impact and insights. Responsibilities include exploratory analysis, model building, and maintaining datasets for student success and operational efficiency.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead and scale reporting and analytics in a fast-paced environment, managing a US and India-based team while delivering insights and resolving bottlenecks across data workflows.