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

Own end-to-end reconciliation and reporting for card networks, banks, processors, and internal ledger data. Build SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigate discrepancies, improve data quality, support month-end close and audits, and partner with Engineering, Product, Accounting, Treasury, Tax, and Compliance. The role also defines requirements and test plans, maintains data pipelines, mentors analysts, and drives automation across payment settlement and money-movement processes.

Own growth and product analytics across activation, retention, adoption, and expansion. Analyze pricing, packaging, monetization, cohorts, and experiments; build instrumentation, measurement infrastructure, AI-assisted scripts, agents, and automation; and turn insights into shipped product or growth changes. Partner with growth, product, pricing, and engineering while establishing data quality standards and trusted metric documentation.

Owns end-to-end data engineering, including scalable pipelines, ELT workflows, analytics data models, cloud-based processing, data quality, governance, logging, anomaly detection, and experimentation measurement. Collaborates with product, engineering, analytics, and data science teams to deliver reliable, production-grade data solutions.

Lead Philo's Data team, overseeing data science, engineering, and analytics to provide reliable insights and data-driven solutions across the company.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Design and implement scalable data pipelines and a SOC2-compliant data warehouse. Support analytics and ML teams, enable real-time and batch ETL, mentor data engineers, and collaborate cross-functionally to drive data-driven decisions.

The Data Analyst will generate client reporting using Python and SQL, maintain reporting scripts, conduct quality checks, and enhance data quality for performance analysis.

The Forward Deployed Accountant leads the deployment of AI Agents for corporate accounting, trains teams, and ensures proper configuration and documentation of automated workflows.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.