Top Senior Analysis Reporting Jobs in Madison, WI

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Architect, build, and maintain Snowflake-based ELT pipelines and production data models. Implement observability, data quality, and governance; optimize cost and freshness. Partner with Analytics, Product, and Engineering, use dbt/CI-CD and AI-assisted tooling, and participate in reviews and architecture planning to support analytics, BI, and ML.

Design, build, and maintain enterprise Power BI dashboards and data models. Integrate multiple data sources, write DAX, ensure data quality and performance, support stakeholders with requirements, documentation, governance, and ad hoc analytics to enable operational and executive decision-making.

Design, build, and operate the credit fund's end-to-end data and automation stack. Implement deal workflow, ingest borrower financials and payment telemetry, develop Python credit scoring and forecasting models, ship audit-grade investor and borrower dashboards, enforce security and auditability, and move into portfolio monitoring and underwriting while presenting results to LPs and borrowers.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

The role involves analyzing complex pricing strategies, conducting data-driven analyses, collaborating with cross-functional teams, and translating insights into strategic business recommendations.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead architecture and evolution of Cardlytics' AWS-based data compute platform and lakehouse. Define standards for batch, streaming, ML, and AI workloads; build semantic layer, feature store, and governance. Partner with analysts and engineers, drive CI/CD (Terraform, GitHub Actions), monitoring, security, cost governance, and incident response while mentoring teams and shaping platform strategy.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.