Senior Fraud Data Analyst - Commercial Fraud Operations Analytics Lead - Remote

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Optum Financial prevents and responds to fraud to protect customers and the business. The Senior Fraud Data Analyst serves as the analytics workstream lead for Commercial Fraud Operations, supporting the Commercial Payments line of business. This role leverages advanced analytics, machine learning, and AI-enabled insights to support fraud monitoring, investigations, risk decisioning, and loss mitigation across Commercial Payments products and channels. In partnership with Commercial Fraud Operations, Product, Technology, and Risk stakeholders, the individual will define requirements, build scalable reporting and analytics solutions, evaluate fraud detection performance, and identify opportunities to improve operational effectiveness and fraud outcomes. 'Lead' reflects ownership of analytics delivery, stakeholder alignment, and prioritization of workstreams rather than direct people management.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities:

• Fraud Analytics Strategy & Delivery (Workstream Lead)
  • Lead intake, prioritization, sequencing, and delivery coordination for fraud analytics initiatives supporting Commercial Payments, managing multiple concurrent stakeholder requests and dependencies
  • Translate business objectives into measurable analytics deliverables, ensuring timely execution and adoption of solutions
  • Define business requirements and delivery priorities for scalable fraud analytics capabilities, partnering with Product, Technology, Data Science, and Fraud Operations stakeholders to deliver actionable fraud intelligence, performance insights, risk monitoring, and decision support across Commercial Payments
• AI-Driven Fraud Detection & Optimization
  • Partner with Commercial Fraud Operations, Product, and Technology teams to develop, evaluate, and optimize fraud detection strategies utilizing rules, predictive analytics, machine learning models, and AI-enabled monitoring capabilities
  • Evaluate model and rule performance using key measures such as precision, recall, false positive rates, fraud capture rates, and operational impact
• Data Analytics, Insights & Risk Mitigation
  • Analyze large, complex datasets containing transaction, fraud case, operational, and customer data to identify emerging fraud trends, root causes, and control opportunities
  • Deliver actionable recommendations that reduce fraud losses, improve operational efficiency, and strengthen risk controls
  • Define requirements and support development of a commercial payments fraud intelligence repository or data product that consolidates information from multiple sources to build fraud profiles, identify emerging threats, and support fraud detection, prevention, investigation, reporting, and risk mitigation activities
• Performance Reporting & Executive Storytelling
  • Design and maintain enterprise dashboards and reporting solutions using tools such as Power BI or Tableau
  • Communicate analytics findings and business implications through executive-ready presentations, supporting operational, product, and risk management decisions
• Analytics Automation & AI Enablement
  • Support basic data architecture and engineering needs by building foundational reports, datasets, and pipelines that convert bronze medallion tables to silver and gold, creating the infrastructure needed for scalable reporting, dashboards, and advanced analytics
  • Develop and maintain automated analytics workflows using SQL, Python, AI-assisted analytics tools, or related technologies to improve reporting scalability and efficiency, including use of generative AI tools to write, review, and debug code where appropriate
  • Identify opportunities to leverage generati