Top Data & Analytics Jobs in Minneapolis, MN

The Senior FP&A Manager will guide strategic financial decision-making, create business cases, and benchmark operational performance while partnering with stakeholders across the organization.

Produce routine and ad hoc credit risk reports and analytics for senior management and regulators. Validate and integrate data, maintain operational and reference data integrity, develop reports and data-quality processes using Cognos and Power BI, and serve as LOB liaison on reporting, metadata standards, and special projects.

The Business Insights Manager conducts analysis and provides strategic insights to guide decision-making, integrating market, financial, and operational data to inform commercial strategies.

The Sr. Data Quality Analyst will focus on data testing, analysis, and SQL skills, with expertise in Informatica and collaborative problem-solving.

The Associate Director develops and executes pricing strategies, analyzing market dynamics, leading pricing initiatives, and ensuring compliance in the pharmaceutical industry.

Lead design, build, deployment and maintenance of SSIS/ETL processes and SQL Server databases for the enterprise data warehouse. Develop consumption views, troubleshoot ETL failures and data integrity issues, support DB administration, backup/disaster recovery, create data migration code, and provide on-call database problem resolution while coordinating with business users and vendors.

Support research staff on secondary government data projects, survey programming, data collection/panel management, and reporting. Assist with client and syndicated project deliverables and maintain records; attend company meetings.

Support Pet Channel and Burt's Bees Target team with sales forecasting, KPI tracking, volatility/risk analysis, and regular sales reporting. Translate data into actionable insights, partner with account managers and sales leadership, and drive customer strategy through analytics and stakeholder communication.

Lead analytics across business programs, delivering insights, forecasts, dashboards, and governed datasets. Partner with Data Science, Product, and Engineering to define measurement, build pipelines, monitor model health, and produce executive-ready recommendations. Establish analytics and AI best practices, mentor analysts, and replace manual processes with automated reporting and decision analytics.

Lead architecture, implementation, QA, and validation of server-side tagging, pixels, and CAPI integrations. Partner with client engineering for requirements and UAT, monitor vendor pixel changes, document implementations, and support internal reporting/data quality and stakeholder training.