Top Data & Analytics Jobs in Ann Arbor, MI

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

The role involves project management, efficiency analysis, quality assurance, and systems management with a focus on improving operational workflows and processes.

Lead data architecture and strategy across product, data science, and engineering. Design cloud-centric, scalable data models, ETL/ingestion, governance, and AI/ML-ready analytics. Guide tooling selection, proofs-of-concept, data storage decisions, security/compliance, documentation, and mentor Data Platform team members to operationalize mission-critical data solutions.

Lead data strategy, analytics, predictive modeling, and contact-center systems operations for Liveops' largest healthcare client. Manage analysts, data scientists, and systems engineers to optimize Five9 and Virtual Observer environments, drive predictive insights, improve patient journeys, and present findings to clients and senior leadership.

Own marketplace analytics and attribution, build source-of-truth dashboards, define and instrument product/growth metrics, run A/B experiments end-to-end, perform cohort LTV/payback analysis, support SEO and technical growth, and partner with AI to measure feature impact and accelerate analytics with AI tools.

Partner with cross-functional teams to analyze large healthcare datasets, build models and dashboards, and surface insights to reduce medical waste. Scope, run, and present analyses, monitor performance metrics, and support initiatives to improve financial and utilization outcomes.

Build and maintain dashboards and reports (Excel, Tableau, Sigma) by pulling and modeling production data (SQL, Python). Create pricing models for RFPs, define operational and financial metrics, optimize queries and data structures, run A/B experiment analyses, and partner with business leaders to generate insights and recommendations to improve roadside assistance operations and performance.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

Lead and build PushPress's data and AI foundation: define data strategy, architect pipelines and warehousing, ensure data quality and governance, enable AI product features, deliver analytics and reporting, and hire and grow a high-performing data team.

Execute financial models and pharmacy claims analyses to support underwriting for sales bids, present results to stakeholders, recommend pricing adjustments, drive pricing research, improve processes, and run quality control on analyses.