Top Remote Analysis Reporting Jobs in Minneapolis, MN

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

Lead a team delivering actuarial, regulatory, and operational statistical reports and analytics. Ensure compliance with bureau submissions, drive reporting automation, define data requirements, lead UAT for policy/claims systems, and manage vendor and regulator interactions to support pricing, reserving, underwriting, claims, and financial analytics.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

Build and maintain P&C actuarial pricing models and indication reports; refine pricing methodologies; analyze large datasets; automate workflows with Python, SQL, and Excel; create dashboards and presentations; collaborate with underwriters, claims, program teams, and reinsurers; and drive process and methodology improvements.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

Lead data strategy for Stripe's risk product, design metrics and frameworks, manage data reliability, mentor analysts, and evaluate risk experimentations.

Own operational health, governance, and integrity of GTM customer and prospect data across Salesforce, Marketo, Demandbase and integrated systems. Implement data quality programs, manage enrichment and integrations, troubleshoot sync failures, support segmentation and reporting, document standards, and enable scalable automation and AI workflows to support Marketing, Sales, Customer Success, and Analytics.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.