Top Data Analyst Jobs in San Francisco, CA

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

As a Lead Data Analyst, you'll optimize transaction costs and success rates in payments, analyze failure patterns, and collaborate with Data Science and Engineering to enhance payment strategies and model performance.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

The Principal Revenue Data Analyst will build analytics and automation for finance controls, create data models, dashboards, and ensure data quality while collaborating cross-functionally.

The Compensation Data Analyst ensures data accuracy and integrity for compensation insights, troubleshooting data issues, and collaborating with various teams to maintain data quality.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

As a Data Analyst, you'll drive data insights for product development at Grow Therapy, supporting reporting and experimentation projects.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Partner with product squads to own end-to-end analyses: define questions, write SQL, model event-level data, build dashboards and self-serve tools, evaluate experiments, and deliver clear, actionable recommendations to PMs, marketers, and leaders.

Develop, test, and maintain analytics and reports for pharmacy operations. Translate designs into code, validate reports, document business rules and logic, and support ad-hoc and workplan analytics using SQL and Tableau.

Senior Data Analyst with 7+ years experience performing data profiling and analysis, strong SQL/Oracle skills, and required healthcare or life sciences domain expertise. Responsible for analyzing data quality, profiling datasets, querying for insights, and communicating findings. 6-month contract; strong communication skills required.

The Data Analyst will reconcile financial data, normalize customer data, support cross-functional teams with data insights, and enhance data architecture and pipelines.

Support program planning and policy by collecting, analyzing, and reporting data; develop reports and dashboards; maintain data systems and ensure data quality; research and integrate data from multiple sources; provide recommendations, training, and technical support to staff; and support enhancements to reporting processes and analytical tools to improve organizational effectiveness.

Owner of Support Operations analytics: build and maintain dashboards and recurring reports, track cSAT/TTR/QA/escalations, instrument Zendesk, connect support to product/customer data, design feedback loops, measure AI-driven support impact, quantify cost of bugs/features, and support ad-hoc analysis for leadership.

Collect, clean, and analyze data to support business decisions; build dashboards and reports; identify trends and insights; and present findings to stakeholders. Maintain attention to detail and apply problem-solving to derive actionable recommendations.

The Lead Data Analyst will oversee marketplace analytics, define operational metrics, clean data, conduct user behavior analysis, and partner with leadership to drive product strategy and revenue growth.

Provide data-driven insights for mass tort and product liability litigation by building predictive models, financial projections, and dashboards; manage litigation portfolios, collaborate with attorneys and finance, and translate analytics into strategic recommendations to guide case valuation, settlement strategy, and practice profitability.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.

Support cost management and project controls for data center construction by aggregating, cleaning, and analyzing cost and schedule data; build EAC templates, dashboards, and executive reporting; perform benchmarking and reconcile multi-source datasets; establish baselines and unit rate libraries; communicate insights to technical and non-technical stakeholders and assist with ad hoc analyses.

Support healthcare research projects by cleaning, managing, modeling, and visualizing large claims and survey datasets (e.g., CMS, MEPS). Produce statistical analyses, documentation, and client-ready reports using SAS and Python/R while following quality assurance and project timelines.

The Senior Marketing & Data Analyst will lead complex analytics projects, perform data analysis and reporting, ensure data integrity, and provide actionable insights based on market data to optimize business processes and inform decision-making.

As a Data Analyst Intern, you will assist in data collection, cleaning, analysis, and visualization to support business decisions in a remote setup.

Analyze large training and telemetry datasets using SQL and Python to measure ROI and human risk, build executive dashboards in Looker/Tableau, audit data integrity, run behavioral analyses to identify high-risk cohorts, and present actionable insights to federal stakeholders while partnering with Data Engineering and Product.