Top Data & Analytics Jobs in Detroit, MI

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

The role involves leading global forecasting and performance management, setting standards, overseeing processes, collaborating with cross-functional teams, and developing a high-performing team in the oncology biotech sector.

Analyze sales data, build and maintain dashboards and scorecards (Power BI, Excel), evaluate market trends, employ AI/automation for pipeline and lead scoring, support sales leadership with actionable insights, document processes and collaborate cross‑functionally to improve sales performance and planning.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Partner with GTM, Clinical Strategy, and Finance to build and maintain dbt models, client-facing reports, and dashboards. Perform SQL-based analyses, ROI and clinical outcomes reporting, and translate insights for non-technical stakeholders. Ensure data reliability through testing, code review, and collaboration with Data Engineering; support ad-hoc requests and automation of reporting.

Lead a high-impact analytics function partnering with clinical and business leaders to apply advanced analytics, modeling, and BI to improve participant outcomes, operations, and financial performance. Manage and mentor analysts, design analyses and models, build stakeholder relationships, and communicate actionable insights to influence enterprise strategy.

Lead design, implementation, and operation of a scalable, secure cloud data platform (data lake/warehouse/lakehouse). Build data pipelines, migrations, archival, IaC provisioning, CDC-enabled ingestion, governance, multi-tenant security, DR/HA, and performance optimization to support reporting, analytics, and AI/ML for a federal judiciary modernization program.

Design, build, and maintain scalable cloud data pipelines and ETL/ELT processes using Azure Data Factory, Snowflake, SQL, and Python. Integrate enterprise and third-party data, validate and model datasets for BI, reporting, automation, and AI, monitor and optimize pipeline performance, and document data flows while partnering with stakeholders.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Support JDA/Blue Yonder WMS, configure systems for customer implementations, test new code, and collaborate with teams for operational improvements.