Top Data & Analytics Jobs in Madison, WI

Lead the development of analytics solutions across operations, manage a team of analysts, and drive operational excellence and decision-making through data insights.

The Risk Analyst will develop strategies to mitigate fraud risk, analyze data, and collaborate with various teams to support low friction customer experiences. Responsibilities include reviewing accounts, creating analytical models, and reporting on progress against business goals.

Manage and validate financial models, ensuring accuracy and compliance. Collaborate across teams to improve model performance and frameworks.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

The Business Intelligence Lead will build and refine measurement systems, translating business objectives into metrics, ensuring data accuracy, and providing insights for strategic decision-making.

As a Product Data Analyst, collaborate with cross-functional teams to analyze product usage data, define KPIs, and support data-driven decisions to enhance customer experience and product performance.

The Senior Data Engineer will design and implement data architectures and pipelines, ensure data quality, automate processes, and collaborate with stakeholders to provide actionable insights using AI and big data technologies.

The Principal Fraud Analyst will lead risk framework evolution, develop fraud metrics, collaborate on scalable solutions, and enhance risk detection capabilities in payments.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.