Top Data & Analytics Jobs in Ann Arbor, MI

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.

Designs, develops, maintains, and optimizes complex data systems, SQL databases, ETL processes, data warehouses, reports, and .NET applications supporting pharmacy benefit management. Responsibilities include database performance tuning, troubleshooting pharmacy claims processes, developing scalable solutions, documenting technical designs, participating in Agile ceremonies, collaborating with stakeholders, mentoring teammates, and ensuring healthcare data compliance.

Build relationships with AWS sales teams across U.S. territories, source AWS-originated opportunities, qualify customer modernization needs, articulate Mactores’ business value, and coordinate technical handoffs to forward-deployed engineers. Maintain opportunity registration in ACE, keep AWS representatives informed through deal close, attend partner events, and provide market feedback to leadership. The role focuses on qualified pipeline and revenue rather than activity volume.

Build and optimize Hipp’s analytics data platform, including production data pipelines, warehouses, schemas, dashboards, reports, and data models. Write complex SQL, monitor data quality, perform product and operational analysis, and translate business needs into technical solutions. Collaborate with product managers and data scientists to support AI and ML initiatives, deliver reliable insights, and inform product strategy.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

Leads commercial analytics and business intelligence strategy, including executive dashboards, account reporting, revenue and pricing analytics, operational KPIs, forecasting, segmentation, and predictive modeling. Partners with Sales, Finance, Marketing, Operations, and Product to improve revenue, profitability, customer retention, and marketplace performance. Presents insights to executives and customers while managing analytics teams, budgets, vendors, and BI scalability.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Build and maintain research data infrastructure connecting laboratory instruments, analysis pipelines, LIMS, repositories, databases, and cloud platforms. Develop ingestion and data transformation pipelines, manage metadata and persistent identifiers, deploy Kubernetes-based services, maintain CI/CD and infrastructure-as-code, and integrate AI/ML tools for data discovery. The role also evaluates data-management technologies, trains research staff, and produces technical documentation and procedures.