Top Data & Analytics Jobs in Ann Arbor, MI

The Senior Growth Analyst will lead data analytics efforts, develop BI dashboards, engage stakeholders, and ensure data governance within healthcare analytics.

The Business Systems Analyst translates business needs into system requirements, ensuring effective data governance, AI readiness, and operational efficiency across Teachstone's systems.

The Data Migration Specialist plans and executes data migrations for EvenUp, ensuring accurate and secure data transfer into their platform and supporting customer adoption.

Support and advance rating tools, conduct technical analyses for insurance pricing, manage portfolio performance, and mentor junior analysts.

The Facets Systems Analyst will perform development and maintenance tasks in Facets, lead a team of developers, and ensure quality outcomes through testing methodologies while maintaining compliance with healthcare standards.

The Business Operations Analyst will centralize and improve corporate reporting and business intelligence while executing data acquisition for patient data initiatives. Responsibilities include metric compilation, dashboard design, and data analysis across multiple teams.

As a Data Analyst at Solace, you will drive operational excellence by identifying inefficiencies, build scalable analytics systems, and communicate data insights to help the business scale effectively.

Lead design, planning, execution, and quality oversight of clinical trial data management (Phase I-IV). Manage CROs and vendors, ensure EDC/eCRF/ CDM standards, support database locks/snapshots, collaborate with Biostatistics/Programming and other functions, and maintain regulatory-ready documentation for submissions.

As a Staff, Advanced Analytics, New Business, you'll analyze data for new business extensions, collaborate with teams, define metrics, and conduct A/B tests to drive strategic decisions.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.