Top Data & Analytics Jobs in Detroit, MI

As an Analyst in the Insights and Analytics team, you will analyze data to boost audience understanding, enhance revenue strategies, and support sales initiatives through actionable insights.

The Senior Product & Growth Analyst will lead the analytics behind Trust & Will's growth, focusing on conversion, retention, and lifetime value analysis. Responsibilities include building predictive models, conducting experimentation, and delivering data-driven recommendations to stakeholders. The role involves collaborating across product, marketing, and growth teams, with a strong emphasis on user behavior and funnel analysis.

Lead and enhance Stripe's analytics infrastructure by setting standards, solving complex data challenges, improving data quality, and driving technical vision across teams.

The Sr. Global Planning Manager drives sales planning processes, supports cross-functional enablement, and leverages data analytics for revenue operations, focusing on tool implementation and insights generation.

The Sales Analyst analyzes sales performance, develops reports and dashboards, supports forecasting and pipeline management, and collaborates cross-functionally to drive revenue growth.

The Control Tester - Data & AI Governance leads testing activities for Data and AI Governance controls, assessing their effectiveness, documenting findings, and communicating with stakeholders.

As an Analytics Engineer, you'll own analytics solutions from data architecture to visualization, ensuring streamlined insights for business stakeholders.

The Data Engineer II will optimize, support, and deploy SQL Server environments in cloud settings, enhance data platforms, mentor junior engineers, and collaborate across teams.

The Senior Enterprise Performance Analyst will develop dashboards, analyze performance data, support decision-making, mentor junior analysts, and improve organizational performance.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.