Top Analytics Jobs in Detroit, MI

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Build and maintain production data pipelines, dbt models, Airflow workflows, and governed datasets supporting People Analytics. Integrate Workday and other HR systems into reliable Snowflake data products, implement data quality monitoring, row-level security, semantic models, and AI agents. Partner with engineers, analysts, data scientists, and business stakeholders to deliver trusted data solutions, communicate technical trade-offs, enforce governance, and mentor other engineers.

Own the people analytics roadmap, build reliable HR data pipelines and reporting, and deliver workforce, talent, and process insights. Analyze employee lifecycle operations, measure performance, identify automation opportunities, and develop dashboards and predictive analyses for senior leaders. Partner across People, HRIS, IT, Finance, Legal, and data teams to improve data governance, privacy, operational efficiency, and employee experience. Establish analytical standards and coach People colleagues on data-driven decision-making.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Lead Toast’s global People Analytics function across data engineering, analytics, data science, and employee listening. Set the people data and reporting strategy, establish trusted metrics and governance, partner with executives on workforce decisions, measure People program impact with Finance, and build scalable self-service analytics. Manage a distributed US and India team, oversee executive and board-level workforce analysis, and collaborate with privacy, legal, People technology, AI, and data engineering teams.

Leads strategy, planning, and execution of customer EMR integrations for PhareOS. Oversees end-to-end data delivery, integration quality, process standardization, tooling, vendors, and platform enhancements. Builds and scales the data integration team, manages resources and senior client stakeholders, and drives innovation across integration methods and operating models. Requires extensive healthcare data integration leadership, HL7/FHIR and interface engine expertise, SQL proficiency, and strong program management skills.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

Designs, develops, and maintains scalable data pipelines using Spark, SQL, Python, and Databricks. Transforms and integrates data, implements quality monitoring, collaborates with data scientists and analysts, documents workflows, and follows software development practices including Git, testing, code reviews, and CI/CD.

Supports data pipeline development, data modeling, wrangling, semantic layers, dashboards, and reporting using SQL, Python, AWS, and Snowflake. Collaborates with cross-functional teams to translate business requirements into data solutions and applies data governance, security, and quality practices. This co-op is designed for a currently enrolled university student available January 11 through June 25, 2027, and willing to relocate to Framingham, Massachusetts.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.

Teaches undergraduate and graduate data analytics courses in an online, technology-enhanced format. Develops syllabi, lesson plans, course materials, assessments, and grading criteria; facilitates learning and provides timely feedback. Integrates responsible AI use, data ethics, and appropriate technology into instruction. Requires a relevant doctorate, applied analytics experience, strong communication skills, and expertise with analytics tools, methodologies, governance, and responsible data practices.

Build scalable Python backend services, data pipelines, and analytics platforms supporting fraud attribute development, machine learning model development, deployment, and monitoring. Design maintainable production systems, implement CI/CD and infrastructure as code, manage AWS and on-premises environments, improve reliability and security, troubleshoot pipelines, and process large datasets for analytics and visualization.

Develops scalable analytics, dashboards, reporting, datasets, and decision-support solutions for Hub leadership. Translates ambiguous business questions into analytical approaches, KPIs, and actionable recommendations using SQL, Power BI, and Databricks. Supports data governance, stewardship, quality, definitions, documentation, and trusted data assets while partnering with Technology and business stakeholders to build future analytics capabilities.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

Leads analytics for a designated sub-vertical, serving as the primary analytics partner to Sales and senior clients. Translates ambiguous business questions into actionable insights, manages analytic engagements, supports partner performance, and influences campaign strategy. Uses SQL, AI tools, and compelling storytelling to deliver analysis, QBR narratives, measurement frameworks, and recommendations. Represents analytics in cross-functional and external discussions while helping prioritize team capacity and evolve scalable analytic processes.

Leads the strategy, development, and delivery of client-facing reporting and analytics for life sciences clients. Builds Power BI dashboards, automated reporting, self-service analytics, KPI frameworks, and data governance standards. Translates commercial, medical, operational, claims, prescription, and client data into actionable insights. Partners with technical and business stakeholders, manages reporting priorities, vendors, budgets, and project delivery, and presents findings to executives and clients.

Leads technical operations for analytics and business intelligence systems. Designs architectures and solutions across data warehouses, BI tools, APIs, AWS, and Talend; oversees system changes, monitoring, security audits, and technical debt remediation. Collaborates across departments, implements coding standards, identifies downstream impacts, and mentors team members developing reporting applications.

Performs descriptive and prescriptive analytics on healthcare transaction data, including data extraction, cleaning, feature creation, exploratory analysis, validation, dashboarding, and reporting. Translates business questions into analytic tasks, supports product discovery and MVP prototypes, profiles data sources, reviews ETL processes, and documents reproducible methodologies. Partners with engineering, product, analytics, and commercial teams while maintaining data privacy, governance, quality, and clear communication for technical and non-technical audiences.

Build and maintain scalable analytics data products using SQL, dbt, Snowflake, and dimensional modeling. Design trusted warehouse tables, semantic layers, metrics, dashboards, and self-service tools for BI, data science, machine learning, and AI use cases. Partner with stakeholders, optimize performance and costs, enforce data governance and privacy, improve data discovery and lineage, and mentor teammates through collaborative development and code reviews.

Analyze lifecycle marketing performance, develop measurement and attribution frameworks, optimize campaigns and customer journeys, and connect marketing activity to product and business outcomes. Partner with marketing, product, engineering, and data teams to improve analytics capabilities, use AI-powered techniques for predictive insights, and present recommendations to senior leadership.

Owns sales and creator-commerce data end to end, building tested and documented dbt models, semantic-layer metrics, and Omni dashboards. Partners with Sales, RevOps, Product, and data engineering to model CRM, pipeline, funnel, commerce, and product-usage data. Establishes trusted metric definitions, improves self-service reporting, enables AI-assisted data querying, reviews code, documents decisions, and serves as the primary owner of Kit’s sales data domain.

Own the architecture, technical direction, reliability, and evolution of a shared cloud data platform. Lead hands-on development of streaming and batch pipelines using infrastructure-as-code, build governed analytical data products, and establish data contracts, quality, security, lineage, and observability standards. Serve as the final technical escalation point, mentor engineers, lead design and code reviews, promote responsible AI-assisted coding, respond to incidents, and communicate technical tradeoffs across stakeholders.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.