Top Senior Analytics Jobs in Ann Arbor, MI

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.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

Lead an analytics implementation for Valvoline's Global Products segment, driving metrics standardization, reporting consistency, and data accessibility. Create a scalable data framework, improve decision-making through visual analytics, and coach internal teams on analytics best practices.

The role involves leading analytics solutions for Valvoline's Global Products segment, implementing a comprehensive data framework, and enabling insights through effective visualization and analytics practices.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

Lead a team of analysts in Fraud & Safety operations, defining KPIs, designing experiments, optimizing performance, and enabling data-driven decisions globally.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead implementation, enhancement, and QA of digital analytics and tag management solutions (primarily Adobe). Design data layers, implement marketing pixels, configure tracking, validate analytics, support Adobe Target integrations, and consult with stakeholders on requirements and strategy.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Lead intake, grooming, and translation of reporting and analytics requests into actionable requirements. Drive stakeholder sessions, define data logic and metrics, prioritize requests, enable scalable reporting solutions, support delivery and UAT, mentor junior analysts, and improve intake processes to reduce one-off requests and promote reusable, self-service reporting.

Build scalable GTM and product analytics to inform revenue, retention, and growth decisions. Partner with Sales, Customer Success, Finance, Product, and Data Engineering to deliver dashboards, models, and executive data stories; validate data quality; measure ROI; and enable self-service reporting across the lead-to-quote-to-cash journey.

Design, build, and maintain ETL/ELT pipelines and analytics data models from structured and event-level data. Transform clickstream/telemetry into user-level journeys, implement dbt transformations in a cloud warehouse (Redshift/Snowflake/BigQuery), develop reverse ETL workflows, enforce CI/CD/version control and automated data quality tests, and partner with BI, marketing, and product to deliver dashboards and attribution reporting.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

Own and build scalable analytics models, metric definitions, and dashboards (customer-facing and internal). Partner with engineering to design data flows and instrumentation (BigQuery, S3, PostHog). Translate stakeholder needs into analytics plans, triage requests, and surface insights via Looker/Observable. Set analytics stack direction and ensure data quality.

Lead complex analyses of large healthcare datasets to evaluate growth opportunities, measure test-and-learn results, build dashboards and automated reports, enable self-service analytics, and present actionable insights and recommendations to stakeholders to drive pharmacy prescriptions and immunizations growth.

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.

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 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.

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.