Top Senior Analysis Reporting Jobs in Madison, WI

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.

As the Director of Analytics, you'll lead analytics for MyPrize, optimizing performance across teams, developing reporting tools, and informing data infrastructure.

The Senior Product Analyst will oversee product analytics projects, collaborating with teams to develop KPIs, conduct A/B testing, and provide data-driven insights to enhance decision-making.

The Senior Data Analyst will conduct quantitative analysis, optimize products through data insights, and lead A/B testing in collaboration with various stakeholders.

Senior member of the Data & Analytics team who translates operational reporting requirements into Epic- and Qlik-based analytics solutions. Develops RW SQL reports, Radar dashboards, and self-service artifacts; validates data, mentors junior analysts, enforces best practices, supports intake/prioritization, and coordinates training and legacy-to-new-tool migrations.

Lead and scale the enterprise data hub: manage the data warehouse, build reliable ingestion and transformation pipelines, implement governance and data modeling best practices, deliver GTM-ready metrics, enable AI/ML use cases, prioritize the data roadmap, and lead/mentor a data engineering team.

Own and evolve the data platform: architect, build, and maintain data models, pipelines, and access layers. Ensure data quality, governance, and reliability; monitor and optimize infrastructure; provide technical leadership, code reviews, and collaborate with cross-functional teams to deliver scalable data solutions for operations and analytics.