Top Analytics Jobs in Ann Arbor, MI

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Senior technical leader defining Subaru of America's enterprise data architecture strategy across platforms, integration, governance, analytics, and security. Shapes 3-5 year data strategy, drives architecture standards, enables AI/agentic workflows, leads cross-functional solutions, mentors teams, and represents SOA externally to advance data capabilities and compliance.

Inovalon seeks candidates to join their Talent Community, emphasizing data-driven solutions to enhance healthcare outcomes and economics.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Lead retail analytics to identify growth and efficiency opportunities, build strategic recommendations (store footprint, pricing, omnichannel), conduct market/competitive research, drive cross-functional initiatives, and deliver executive-ready analyses and frameworks to inform retail and digital strategy.

Lead building a data- and AI-enabled growth engine to improve pipeline quality and visibility. Define data governance, segmentation, scoring, and KPIs; operationalize demand-generation campaigns and tooling; prototype AI-driven automation and reporting; partner with vendors and sales/marketing to measure and improve pipeline conversion and ROI.

Ensure accuracy, integrity, and compliance of master and reference data across enterprise systems. Enforce governance, validate and remediate Salesforce and other system records, perform audits/cleansing/de-duplication, support migrations and integrations, produce reports and insights, and partner with global teams to improve data processes and adoption of standards.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

Lead analytics engineering for Revenue, Marketing, and Finance by building scalable data solutions, data models, and dashboards; provide training and consultation, support ad hoc data needs, and translate technical findings into executive-level insights to improve operational performance.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

Manage digital commerce analytics for e-commerce channels: own reporting, analyze sales/traffic/conversion/SKU performance, produce dashboards and presentations, support account managers, conduct promotion post-analysis, assist customer planning and deduction resolution, maintain data governance and reporting processes, and support cross-functional analytics projects.

Lead embedded BizOps analytics for a core business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, and drive data-informed recommendations end-to-end to influence leadership and deliver measurable business outcomes.

Own the end-to-end analytics function embedded in a core business area (growth, product, AI, partnerships). Define problems and metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive outcomes with cross-functional teams.

Design, build, and maintain cloud and on-prem data warehouses, data pipelines, and ETL/ELT workflows (Snowflake, SQL Server, Airflow, DBT, Python). Ensure data quality, performance, CI/CD, and support analytics-ready datasets for reporting and BI while collaborating with stakeholders and following Agile practices.

Design, build, and maintain enterprise risk analytics and automated reporting (SAS/Python/Tableau). Translate senior stakeholder needs into scalable dashboards, committee reports, and repeatable pipelines, enabling proactive risk insights and automation.

Design and deliver Tableau BI solutions and advanced-analytics to support Collections, Recovery, and Servicing operations. Partner with stakeholders to gather requirements, act as the liaison between operations and development, build multi-layer dashboards and self-service analytics, ensure data governance and quality, develop scalable solutions, and provide ongoing operational and ad-hoc analytical support.

As a Data Scientist in Customer Analytics, you will analyze customer data, measure Cresta's impact through experiments, and build dashboards for insights. You'll collaborate with cross-functional teams and support strategic customer initiatives.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Lead a centralized Decisioning Analytics team to measure and optimize Pega-powered Next-Best-Action decisioning. Own measurement frameworks, ADM performance, transparency, governance, cross-functional partnerships, NBA analysis, roadmap, and team development to drive measurable customer and financial outcomes.