Top Senior Analytics Jobs in Madison, WI

Lead independent validation and governance of credit and fraud models, build automated Python monitoring for model drift and performance, drive remediation with model developers, and liaise with audit and regulators to support Affirm Bank's model risk management.

Design and maintain people analytics reporting, dashboards, and data models; perform advanced statistical analyses and survey design; automate workflows and collaborate with stakeholders to translate insights into actionable recommendations.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead analytics for clinical decision support adoption and engagement: define metrics, query event-level usage, build dashboards, analyze funnels and cohorts, partner with product and cross-functional teams, and translate findings into actionable product recommendations to improve adoption and outcomes.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Perform domain-specific analytics: develop and optimize analytics processes, build data models, reports, and visualizations, support KPIs and forecasts, collaborate with analytics engineering on data pipelines, communicate insights to cross-functional teams, and mentor colleagues.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Lead Databricks-based enterprise data and analytics modernization programs. Define future-state architecture, drive platform modernization, ensure security, scalability, cost optimization, and mentor teams while delivering AI-ready data platforms and governance.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead marketing measurement initiatives (MMM, attribution, incrementality) using causal inference and validation techniques. Partner with marketing, data engineering, and vendors to deliver actionable insights, KPI frameworks, and strategic recommendations that optimize marketing ROI.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

Lead and oversee reporting and analytics; develop/manage critical operational, financial, quality, and compliance reports; collaborate with business leaders to define requirements; monitor metrics and risks; lead/process improvements and projects; mentor and manage analytics staff; perform programming and analysis as needed to deliver scalable, maintainable reporting solutions.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Design, build, and maintain enterprise risk analytics and automated reporting (SAS/Python/Tableau). Translate senior stakeholder needs into scalable dashboards, committee reports, and repeatable pipelines, enabling proactive risk insights and automation.

Lead enterprise analytics initiatives: translate business requirements into scalable data models and transformations; design enterprise dashboards and SSAS/SSRS/Qlik reports; perform advanced SQL analysis; resolve cross-system data issues (including Workday integration); mentor analysts; enforce data governance and reporting standards; manage multiple analytics projects and documentation.

Lead a team to develop data strategy and insights across multiple business functions, driving analytics evolution and ensuring data quality and governance.

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.