Top Remote Data & Analytics Jobs in Ann Arbor, MI

The Junior Manual QA Engineer will execute test cases, perform exploratory testing, document bugs, and collaborate with teams to ensure high-quality software. This role involves learning QA methodologies and improving testing processes alongside experienced professionals.

Lead the Data Engineering team at Docker, focusing on strategic data analytics and platform evolution to enhance product innovation and customer insights.

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

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.

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.

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.