Top Analytics Jobs in Detroit, MI

Develops business intelligence, reporting, data pipelines, dashboards, and geospatial solutions for complex real estate portfolios. Transforms and integrates data from multiple sources, builds scalable analytics products, automates reporting processes, and supports portfolio planning, occupancy strategy, workplace initiatives, and operational decision-making. Partners with stakeholders and clients to translate business needs into technical solutions, communicate insights, train users, and improve analytics adoption. The role also supports geospatial capabilities and leverages emerging AI-enabled tools.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Lead and manage a remote analytics engineering team responsible for Extend’s Snowflake warehouse, dbt repository, ingestion pipelines, data models, monitoring, and quality standards. Oversee hiring and development, architecture, platform migrations, reliability, incident response, documentation, and self-service analytics. Partner with actuarial, risk, fraud, product, finance, and operations teams to establish trusted shared data definitions and prioritize platform improvements.

Leads a multidisciplinary marketing analytics organization spanning data engineering, analytics engineering, visualization, and data science. Builds attribution, ROI, customer journey, predictive signal, data governance, and AI-ready information architecture systems. Partners with Sales, RevOps, Finance, PLG, and Data teams to improve capital allocation and growth decisions. Oversees executive dashboards, metric alignment, team capacity, and strategic analytics delivery.

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

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.

Build and steward Netflix advertising quality-of-experience data, from device telemetry and instrumentation through data pipelines and dashboards. Collaborate with product engineering, data engineering, and data science teams to measure user-perceived performance, improve data quality, document user flows, and establish monitoring and measurement best practices. The role requires strong SQL and Python skills, technical communication, stakeholder management, and comfort working independently in an ambiguous environment.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Lead a global, AI-first Data Analytics and BI organization that integrates internal teams and vendors to deliver proactive, predictive insights. Design the future operating model, own metric governance and semantic layer, consolidate dealer and CX data, and migrate legacy reporting to cloud-native architectures while partnering closely with central tech teams.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; generate actionable insights; communicate recommendations to leadership; and drive execution through measurable outcomes. The role requires independent problem-solving, strong analytical skills, persuasive communication, and ownership of ambiguous, high-impact initiatives.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate insights; and drive recommendations through execution. The role requires strong first-principles thinking, independent data work, persuasive communication, stakeholder influence, and ownership of ambiguous, high-impact initiatives.

Maintains Looker and LookML dashboards, explores, and reporting infrastructure; supports ad hoc analysis, forecasting, sales pacing, data quality, UAT, vendor management, board reporting, and planning materials during a temporary maternity-leave backfill.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Analytics Engineering Intern supporting data modeling, dashboard development, reporting, data quality validation, and business insight generation. The role involves writing SQL, building Looker Studio dashboards, collaborating with stakeholders, presenting findings, and using AI coding assistants responsibly. Candidates must be enrolled in a quantitative undergraduate program and have basic SQL and Git knowledge.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

Designs, builds, tests, and supports enterprise data pipelines for acquired-company system integration and Snowflake archival. Translates business and technical requirements into mappings, transformations, quality controls, monitoring, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams to deliver governed, reusable data solutions. Supports migration, cutover, validation, documentation, hypercare, and operational handoff while improving automation, performance, cost efficiency, and data observability.

Build and maintain SQL-based marketing analytics infrastructure, data models, dashboards, and reporting. Analyze marketing channels, affiliates, conversion funnels, cohorts, revenue, profitability, and partner performance. Translate complex findings into actionable recommendations for budget allocation and optimization. Ensure data quality, governance, documentation, and metric consistency while partnering cross-functionally with Marketing, Sales, Finance, Operations, Product, and Technology. The role is a hands-on individual contributor with potential responsibility for mentoring or managing one analyst.

Leads analytics, data architecture, outcomes measurement, health economics and outcomes research, ROI modeling, governance, and client reporting. Manages a multidisciplinary data team and partners with Engineering, Product, executives, and payer stakeholders to translate clinical and financial evidence into actionable decisions. Oversees accurate, repeatable analyses and communicates findings through dashboards, white papers, presentations, and impact briefs.

Owns the health of a multi-client digital tracking ecosystem across 100+ properties. Responsibilities include managing Piwik PRO and Google Tag Manager configurations, deploying pixels and telemetry updates, monitoring and debugging conversion events, validating implementations with browser tools and APIs, supporting technical client onboarding, managing consent and UTM governance, documenting configurations, and coordinating technical escalations. The role also explains tracking behavior to nontechnical teams and improves automation and monitoring processes.

Own regulatory analytics and reporting by building audit-ready datasets, dashboards, data models, pipelines, governance controls, and compliance automations. Analyze complex financial and compliance data, support audits and risk assessments, monitor data quality, and translate regulatory requirements into reliable reporting solutions using Python, SQL, dbt, and Airflow. Partner with engineering, analysts, compliance teams, and leadership to deliver actionable insights and improve regulatory processes.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.