Top Data & Analytics Jobs in Ann Arbor, MI

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Business Analyst will manage the Quote-to-Cash lifecycle, liaising between IT and functional teams, and ensuring successful implementation of system updates while documenting requirements.

Lead analytics work translating complex healthcare data into decision-ready insights. Own KPI definitions, Snowflake data marts with dbt, executive dashboards in QuickSight, and cross-functional analyses to inform strategy, product, and operations.

Lead client-facing data solutioning and pre-sales efforts for Consumer verticals, design executable data architectures, support pursuit to close, and provide ~50% hands-on delivery and architectural oversight while ensuring information security and data privacy compliance.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

The Analyst II will leverage data analytics to derive insights, optimize credit strategies, and collaborate with cross-functional teams including Machine Learning and Engineering.

Lead digital measurement strategy for web and digital marketing. Build and maintain dashboards, integrate multi-platform data, perform tagging QA, run A/B test analyses, and deliver insights to optimize campaign effectiveness, UX, and ROAS.

This role oversees the design and evolution of finance reporting solutions using Power BI, collaborating with global finance teams to create scalable analytics and insights.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.