Top Data & Analytics Jobs in Ann Arbor, MI

As Senior Manager of IT Commercial Data Management, you will lead data initiatives, manage product ownership, and develop data governance strategies in collaboration with stakeholders, ensuring high data quality and analytics capabilities.

Design and maintain data pipelines for analytics and operational decision-making. Collaborate with teams to ensure reliable data systems and governance, utilizing Python and SQL.

The Director of Reporting and Data Management oversees data infrastructure for Workforce Management, establishing objectives, managing teams, ensuring data storytelling aligns with strategy, and leading predictive modeling efforts.

The role focuses on contract data governance, data migration, reporting, and enhancement of data processes to improve decision-making. It requires collaboration with various stakeholders to implement data solutions and maintain data integrity.

The Senior People Data Scientist will deliver HR reporting and analytics using Oracle HCM and Databricks, focusing on data extraction, analysis, and visualization through Power BI. Responsibilities include ensuring data accuracy, compliance with privacy regulations, and collaboration with HR leaders to drive insights and enhance reporting capabilities.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Director of Machine Learning Science will lead teams in delivering ML solutions, drive innovation in search and personalization, and engage with engineering and product teams.

The Product Sales Data Analytics Specialist will develop data pipelines, build dashboards, monitor data quality, and present analytics insights to stakeholders, influencing business decisions.

The GIS Analyst will evaluate and manipulate GIS data, reconcile geospatial analysis and prepare documentation for various GIS projects in public safety.

The role involves building and maintaining data infrastructure, developing data pipelines, optimizing data models, collaborating with teams to provide actionable insights, and deploying AI-driven solutions.