Top Data & Analytics Jobs in Madison, WI

Partner with Product Insights to lead end-to-end quantitative analyses that shape product decisions. Translate ambiguous questions into rigorous, decision-focused analyses (funnels, cohorts, retention, experiments) and deliver actionable recommendations that influence roadmap and strategy.

Hands-on GA4 analyst contractor managing analytics across multiple clients: diagnose data quality and bot traffic, implement GTM tracking, build Looker Studio dashboards, collaborate with SEO/Paid/Strategy teams, and contribute to internal tooling and measurement improvements.

Build a single source of truth for GTM performance by stitching CRM, website, and marketing data; create account-level engagement scoring, define MQL thresholds, implement ABM tooling, build dashboards and attribution reporting, and integrate AI models and automation to drive sales and marketing decisions.

The Senior Product Analyst will analyze complex data sets to guide product strategies, support game teams, and drive game performance insights through collaboration and robust reporting on game features.

Design and execute advanced analytics and statistical models to support revenue cycle surveillance and risk monitoring. Extract, validate, reconcile, and integrate MHS GENESIS and enterprise repository data. Develop and optimize SQL/Vertica queries, CCL/Discern extracts, dashboards (Power BI, Tableau, SAP BO), and analytic deliverables. Support backend diagnostics, incident/change management, remediation analysis, and stakeholder briefings while ensuring HIPAA and federal data governance compliance.

As an Operations Analyst, you'll develop scalable reporting, model supply and demand, and engage with stakeholders to inform business strategies across markets.

Drive go-to-market revenue analytics and strategy by building forecasts, dashboards, and ad-hoc analyses. Partner with Sales, Sales Ops, and Finance to set targets, quota, and deliver actionable recommendations to executive leadership.

The role involves collecting, analyzing, and visualizing data for investment research, utilizing web scraping, data tools, and data science techniques.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Design and execute HEOR studies (cost-effectiveness, budget impact, real-world evidence) using large claims datasets; collaborate cross-functionally; engage stakeholders; produce scientific deliverables (abstracts, posters, manuscripts); and communicate HEOR insights to support adoption, access, and reimbursement for genetic testing services.