Top Senior Data & Analytics Jobs in Ann Arbor, MI

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

The Senior Data Analyst will analyze digital marketing campaigns, leverage data sources for business decisions, and communicate insights effectively to improve performance and support Media Partners.

Lead alignment of technology and business strategies to improve payments reporting, forecasting, and operational planning. Build and maintain reports, dashboards, and models using BI tools and SQL, perform variance analysis, drive data standardization and quality, support migration to modern reporting platforms, and produce ad hoc analyses to inform decision-making.

Own and evolve revenue systems (Salesforce, CPQ), build and govern the enterprise data platform, drive systems integration and AI enablement, manage HRIS and vendor relationships, and lead a cross-functional team supporting Finance, HR, Sales, Operations, and Customer Success.

Lead analytics strategy and enterprise semantic/reporting layers across QuickSight/Tableau and Redshift/Athena. Partner with data engineering on domain models, enforce data quality/governance, optimize analytics performance/cost, mentor analysts, and communicate insights to executives.

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Own the Finance & Operations data layer: ingest and model data from systems (NetSuite, Ramp, Pigment) into Snowflake/Omni, ensure data quality and metric governance, build dashboards and reports, collaborate with Finance/Ops stakeholders, and automate reconciliation and reporting workflows.