Top Remote Data & Analytics Jobs in Detroit, MI

The IO Psychology intern will support data driven people initiatives in talent and organizational effectiveness, focusing on analytics and employee insights in a corporate environment.

This role involves optimizing Jira for Agile processes, defining standards, driving Agile adoption, and ensuring high-functioning configurations across teams.

Lead the Retention Analytics team by providing insights into subscriber journeys, data analysis for retention strategies, and managing a team of analysts.

The Data Annotation Specialist is responsible for high-precision labeling of 3D retail environments and video feeds, ensuring data integrity and quality for AI training.

The Business Analyst will gather, analyze, and document requirements for health IT solutions, support UAT, and collaborate with stakeholders to improve processes.

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.

Develop and maintain data pipelines and reporting tools, support real-time processing workflows, and collaborate with teams to enhance platform capabilities, utilizing Java, Python, and Groovy scripts.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

The Senior Business Analyst collaborates with stakeholders to optimize Oracle Fusion solutions for Supply Chain Management, focusing on Order Management and Procurement, ensuring process integration and functionality. Responsibilities include requirements gathering, configuration, testing, and supporting post-go-live improvements.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.