Top Senior Data & Analytics Jobs in Detroit, MI

Lead complex analytical initiatives, build executive dashboards and KPI frameworks, perform advanced SQL analysis, forecasting and root-cause analysis, partner with senior stakeholders, improve data governance and BI solutions, and mentor junior analysts to drive operational performance and cost/resource optimization.

Design, build, and maintain ETL pipelines and data warehousing for RCM-focused analytics. Perform gap analysis for new business onboarding, optimize ETL performance, monitor production jobs, partner with development on database and analytics projects, and author technical documentation while supporting deployments and change control.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead and manage institutional research activities: collect, analyze, validate, and report quantitative and qualitative data; support program/course reviews, accreditation, dashboards, and decision-making; supervise a team and manage ad-hoc and ongoing reporting and assessment projects.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

The role involves developing forecast models for oncology products, collaborating with teams, and communicating assumptions for strategic decision-making across the organization.

Support business partners with advanced data insights and subject-matter expertise. Build and maintain reporting pipelines and dashboards, write advanced SQL, perform cohort and forecasting analyses, and deliver recommendations. Partner with stakeholders, run trainings to enable self-serve analytics, and manage projects across teams to measure customer activation, engagement, and product success.