Top Senior Data & Analytics Jobs in Minneapolis, MN

Leads claims cost management reporting and analytics initiatives, including forecasting, variance analysis, KPI reporting, dashboards, scorecards, and self-service analytics using Power BI. Partners with business, finance, operations, and technology teams to improve performance through data-driven insights. Develops automated and scalable reporting solutions, applies Generative AI, manages multiple initiatives, ensures governance and data quality, and mentors team members.

Leads governance and lifecycle management for financial crimes and sanctions screening models, including AI-enabled solutions. Responsibilities include model documentation, monitoring, controls, performance analysis, change management, issue remediation, regulatory support, audit coordination, and AI governance. Partners with risk, technology, operations, data, and audit stakeholders while presenting model effectiveness, risk assessments, and remediation updates to leadership and regulators.

Collects, processes, and analyzes complex datasets to produce actionable insights, automated reports, dashboards, and visualizations. Partners with cross-functional teams to ensure data accuracy, integrity, and effective decision-making. Performs statistical analysis, validates data, improves reporting processes, and coaches stakeholders on data consumption. Preferred experience includes applying AI tools, developing AI-enabled solutions, translating business needs into AI use cases, and following responsible AI practices.

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.

Own and evolve the Azure-based data platform for a large-scale telematics SaaS platform. Build high-throughput IoT ingestion, transformation, enrichment, storage, and analytics pipelines using Cosmos DB, Azure Data Explorer, Azure SQL, Fabric, Event Hubs, and Functions. Design scalable telemetry and multi-tenant data models, ensure pipeline reliability and observability, optimize costs and performance, implement governance and CI/CD, and collaborate with engineering, architecture, product, and leadership teams.

Leads enterprise analytics initiatives, partnering with senior leaders to define business questions, analyze complex datasets, conduct experimentation, develop dashboards, automate reporting, and deliver data-driven recommendations. The role influences growth, customer experience, operations, risk, technology, and banking decisions while mentoring analysts and advancing enterprise analytics capabilities.

Leads global people analytics, HCM reporting, and U.S. compliance reporting using Workday and PeopleSoft. Develops reporting solutions, gathers requirements, manages testing, troubleshoots integrations and workflows, maintains data mappings, and supports data audits. Partners with HR stakeholders on projects, ad hoc requests, privacy reviews, documentation, and training. Oversees reports including EEO, AAP, VETS-4212, California pay data, and other regulatory submissions while improving enterprise reporting processes.

Leads Vizient’s indirect spend data and analytics strategy, operating model, governance, quality standards, reporting, automation, and AI adoption. Oversees data lifecycle management, modeling, integration, categorization, normalization, analytical methodologies, dashboards, and decision-support tools. Manages data and analytics teams, develops reusable assets for consulting engagements, partners with technology and product teams, and supports business development and member presentations.