Top Remote Analysis Reporting Jobs in Detroit, MI

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.

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.

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.

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

As a Quantitative Researcher, apply economic and statistical models to large-scale data, collaborating to solve quantitative challenges across industries.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.