Top Data & Analytics Jobs in Ann Arbor, MI

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Lead study design, survey development, questionnaire quality, data analysis, and client-ready reporting for financial services research. Interpret findings with client teams, translate results into actionable business insights, apply analytical methods, and ensure accuracy, clarity, timeliness, and integrity across multiple projects.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Produces publishable maps, graphs, and visualizations of conflict patterns and analysis outputs. Transforms complex datasets into compelling visual stories, develops visualization guidelines, researches new methods and software, and supports visual brand development. Collaborates with regional experts, media, partners, and external stakeholders, responds to journalist inquiries, ensures data accuracy, and contributes to outreach, reporting, coordination, and communications activities.

Leads Commercial Markets Operations intelligence, business intelligence, analytics, reporting, dashboards, and strategic information initiatives. Manages analysts, develops performance metrics, oversees operational reporting, supports executive decision-making, and drives process improvement. The role also manages resource planning, budgets, stakeholder alignment, SharePoint stewardship, and adoption of innovative information solutions across Sales Operations and Commercial Markets.

Analyze and design enterprise healthcare data solutions using Snowflake and advanced SQL. Perform data profiling, reconciliation, anomaly detection, source-to-target validation, and quality testing across claims, membership, provider, and health plan data. Support data architecture, dimensional modeling, governance, metadata, lineage, cataloging, and MDM initiatives. Prepare data for AI and advanced analytics, translate business requirements into solutions, resolve data issues with stakeholders, and communicate actionable insights while following security and HIPAA requirements.

Analyze business, financial, customer, product, market, and operational data to identify trends and growth opportunities. Maintain KPI, OKR, profitability, and executive reporting dashboards, prepare leadership and Board materials, and develop actionable insights for Sales and Client Success teams. Use data to improve retention, expansion, efficiency, profitability, and customer recommendations while partnering across finance, operations, sales, and executive leadership.

Own Chamber’s central analytics and reporting function for value-based cardiology contracts and clinical programs. Build SQL models, governed metric definitions, a semantic layer, data-quality standards, executive and board reporting, payer deliverables, SLA tracking, and clinical analytics foundations. Establish reporting governance so finance, clinical, and operations teams can self-serve trusted insights. This hands-on player-coach role requires healthcare claims and clinical data expertise, value-based care fluency, and the ability to build a reporting function from scratch.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, and SQL. Supports SQL Server, SSIS, SSRS, and data warehousing environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, enables reporting and AI/ML workloads, and partners with business and IT teams to deliver technical data solutions.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, SQL, and Delta Lake. Supports SQL Server, SSIS, and SSRS environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, applies data warehousing practices, and partners with business users, analysts, and IT teams to deliver reporting, analytics, and AI/ML solutions.