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

Senior Fraud Data Analyst

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 generative AI and advanced analytics capabilities to enhance fraud investigations, monitoring, and operational decision-making
• Governance, Metrics & Documentation
  • Navigate complex organizational processes to obtain approvals for data access, usage, and governance initiatives
  • Establish and maintain standardized KPI definitions, metric libraries, data quality controls, and governance documentation
  • Ensure fraud analytics outputs are reproducible, audit-ready, and aligned with enterprise governance standards

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• 5+ years of experience in fraud analytics, risk analytics, financial crime, payments analytics, business intelligence, or a related analytical function
• 5+ years of SQL with experience querying and analyzing large-scale datasets containing millions of records
• 3+ years of experience with analytics initiatives or cross-functional workstreams, including stakeholder management, prioritization, and delivery accountability
• 2+ years of experience developing analytics solutions using Python, R, SAS, or similar programming languages, with hands-on experience leveraging cloud-based analytics platforms such as MS Fabric, Databricks, Snowflake, Google Cloud Platform or Amazon RedShift
• 2+ years of experience building dashboards and reporting solutions using Power BI, Tableau, or comparable visualization platforms
• Demonstrated experience applying statistical analysis, predictive modeling, machine learning, AI-enabled analytics, or anomaly detection techniques to solve business problems
• Experience defining, monitoring, and improving operational KPIs, controls, and performance metrics
• Experience translating analytical findings into operational recommendations, fraud detection improvements, control enhancements, or measurable risk reduction outcomes
• Experience managing end-to-end analytics delivery, including requirements gathering, data validation, testing, implementation, and post-production monitoring

Preferred Qualifications:

• Professional certifications such as Certified Fraud Examiner (CFE), Certified Analytics Professional (CAP), Certified Financial Crime Specialist (CFCS), Azure Data Scientist Associate, Databricks certifications, or comparable analytics, fraud, or AI credentials
• Experience partnering with Product, Engineering, and Data Science teams to deploy fraud analytics, machine learning models, or AI-enabled capabilities into production environments
• Experience using generative AI tools to support coding activities, including drafting, reviewing, debugging, or improving SQL, Python, or related analytics code
• Experience optimizing fraud detection strategy through rule mining, champion/challenger testing, segmentation analysis, and other optimization methodologies
• Experience with generative AI, machine learning, natural language processing (NLP), or AI-assisted investigation tools in a fraud, risk, or operations environment
• Experience supporting regulatory, audit, compliance, or risk governance reviews within a highly regulated industry
• Experience with Commercial Payments products, including ACH, wire transfers, virtual cards, checks, and emerging payment channels
• Demonstrated ability to operate effectively in ambiguous environments, establish structure where processes, reporting, or analytics capabilities do not yet exist, and influence stakeholders across operations, product, technology, and risk functions

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 - $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.