Top Analytics Jobs in Minneapolis, MN

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.

Own the strategy, governance, architecture, modeling, and reporting foundation for People Experience data. Build governed metrics, semantic and consolidated data layers, dashboards, data catalogs, quality monitoring, and operating processes from the ground up. Manage intake, prioritization, access, privacy, enablement, and self-service adoption while partnering with stakeholders on analytics and future AI capabilities. The role combines strategic program leadership with hands-on SQL, data modeling, reporting, and team mentoring.

Develop and deliver healthcare analytics solutions using Ursa Studio, reusable data models, data marts, and measures. Partner with clients and cross-functional teams to scope engagements, provide consulting and training, maintain documentation and security standards, and contribute scalable analytics components to Ursa’s SaaS and AI-assisted platforms. The role requires strong healthcare data expertise, SQL proficiency, client-facing communication, and knowledge of healthcare regulations and standards.

Lead design of end-to-end analytics and data solutions, produce architecture diagrams and technical designs, guide delivery teams, run client discovery and requirements sessions, support pre-sales and proposals, build reusable frameworks, and manage and mentor a delivery team to ensure quality and alignment to architecture.

Lead pricing strategy and analytics: develop pricing, packaging and monetization recommendations; build forward-looking revenue/volume models; maintain pricing algorithms and reporting; collaborate with Sales, Finance, Marketing and Data teams to implement pricing actions and standardize quantitative outputs.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

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.

Translate web and marketing behavior data into actionable insights: measure website and marketing performance, analyze funnels and journeys, design and evaluate A/B tests, build reports and dashboards, monitor analytics integrity, and partner with cross-functional teams to define measurement and optimization opportunities.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Build and maintain auditable data pipelines in Snowflake and dbt to ensure financial reconciliation and audit readiness. Partner with Accounting, Operations, Engineering, and Reporting to investigate data issues, improve integrations via APIs, and own claim reimbursement and contract sales data workflows.

Lead analytics, reporting, and data warehouse strategy for Respiratory Health. Build KPI frameworks, oversee data governance and quality, translate business needs into scalable data solutions, drive advanced analytics/AI initiatives, and manage a high-performing BI and data enablement team while partnering with IT, Finance, and Operations.

Own and evolve the analytics engineering platform: design and maintain certified dbt models, enforce modeling/testing/documentation standards, build semantic and metadata layers, optimize Snowflake performance, partner with analysts and data engineering to migrate business logic and ensure reliable, AI-ready analytics, and mentor teammates on analytics engineering best practices.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Lead Adobe Analytics architecture and MarTech ecosystem design, implement data layers and tagging across web and mobile, ensure QA and privacy compliance, enable reporting and audience activation, and drive cross-functional measurement and governance for personalization and optimization.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

The Enterprise Performance Analytics Engineer builds and maintains data pipelines and models, ensuring data quality and efficient reporting for analytics teams.

As an Analytics Engineer at Axios, you'll design and maintain data products and visualizations, improving decision-making through actionable insights.

Lead and grow a client-facing analytics team to transform measurement from reporting to strategic advisory. Define measurement strategy, develop scalable frameworks, advise executives, drive vertical analytics, partner with Product and Data teams, and embed AI to improve insight generation and operational efficiency.

Design, build, and operate the credit fund's end-to-end data and automation stack. Implement deal workflow, ingest borrower financials and payment telemetry, develop Python credit scoring and forecasting models, ship audit-grade investor and borrower dashboards, enforce security and auditability, and move into portfolio monitoring and underwriting while presenting results to LPs and borrowers.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.

Lead and mentor an analytics team to design and implement data-driven solutions, align analytics with strategy, manage Agile workflows, build stakeholder relationships, and monitor KPIs to improve healthcare delivery and outcomes.