Top Remote Data & Analytics Jobs in Ann Arbor, MI

Perform hands-on data cleansing, linking, validation, and standardization; monitor and report data quality metrics; identify recurring issues and recommend process or automation improvements; organize and streamline workflows; maintain documentation and data standards; test and provide feedback on tools and AI-assisted features; serve as a point of contact for data integrity questions.

The Staff Financial Analyst will manage budgeting and forecasting, develop financial models, automate reporting, and collaborate across departments to enhance financial operations.

The Capital Analytics Lead will analyze capital, margin, liquidity, and counterparty risk, support regulatory engagement, and produce insights for senior leadership.

The Business Intelligence Analyst will analyze pharmaceutical transaction data, develop visual data models, and collaborate cross-functionally to drive insights and improvements in business strategies.

The Senior Analyst, People Analytics analyzes workforce data, translates business questions into KPIs, and collaborates with various teams to deliver insights and reporting solutions.

As a Revenue Integrity Analyst II, you will audit charges, analyze billing data, ensure compliance, and collaborate with cross-functional teams to improve revenue integrity.

The Lead Quantitative Analytics Associate conducts statistical analyses and builds predictive models, responding to business needs and enhancing existing models. They work with large datasets, ensuring data management and model maintenance, while communicating insights effectively within the organization.

As an intern, you will design and optimize dashboards in Sigma, write SQL queries for data extraction, and use Python for data manipulation, all while collaborating with the data team.

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.