Senior Data Analyst - Remote

Senior Data Analyst supporting UnitedHealth Group's Credit team with data driven insights across credit risk, portfolio performance, underwriting, and loss mitigation in a remote friendly, U.S. based role.

Responsibilities

• Serve as a senior analytics partner to the Credit team, delivering data driven insights across credit risk, portfolio performance, underwriting, and loss mitigation
• Develop, optimize, and maintain complex SQL queries to extract, transform, and analyze large volumes of financial and credit data from enterprise data warehouses
• Use Python with libraries such as pandas and NumPy to perform advanced data analysis, automation, validation, and feature engineering, augmenting SQL workflows
• Design, build, and support interactive Power BI dashboards and reports to present clear, actionable insights to Credit leadership and business stakeholders
• Create and maintain SSRS reports to support operational, regulatory, and management reporting needs, ensuring accuracy and timeliness
• Conduct advanced Excel analysis, including pivot tables, Power Query, Power Pivot, and complex formulas to support ad hoc requests
• Analyze credit metrics such as delinquency, roll rates, charge-offs, recoveries, exposure, and vintage performance to identify trends and risks
• Collaborate with Credit Risk, Underwriting, Finance, and Compliance to ensure reporting aligns with business rules and regulatory expectations
• Validate data integrity and reconcile results across multiple systems to ensure reporting reliability
• Translate complex analytical findings into clear insights and recommendations for both technical and non technical audiences
• Support automation and process improvements to increase efficiency, scalability, and self service analytics within Credit
• Mentor junior analysts and contribute to best practices for SQL, reporting standards, and analytical methodologies
• Ensure adherence to data governance, security, and regulatory requirements specific to banking and credit data

Requirements

• 5+ years of experience in data analytics, with direct experience supporting Credit, Credit Risk, or Lending teams within a bank or financial services organization
• Solid working knowledge of credit concepts including delinquency, charge-offs, recoveries, exposure, vintages, utilization, and portfolio performance
• Advanced Python proficiency with libraries such as pandas and NumPy for data manipulation, validation, automation, and large scale analysis; experience building reusable scripts or pipelines is highly valued
• Expert-level SQL skills with experience writing complex joins, CTEs, subqueries, window functions, and performance optimized queries against large datasets
• Advanced Power BI experience, including data modeling, DAX, custom measures, and executive ready dashboards
• Advanced Excel skills, including pivot tables, Power Query, Power Pivot, complex formulas, and ability to perform statistical or financial analysis
• Hands-on experience developing, maintaining, and supporting SSRS reports in a production environment
• Proven ability to validate data, reconcile across multiple source systems, and ensure high data quality and reporting accuracy
• Strong analytical and problem solving skills with the ability to independently investigate issues and deliver insights
• Excellent communication skills to explain complex data findings to both technical and non technical stakeholders

Technologies

• Python
• pandas
• NumPy
• SQL
• Power BI
• SSRS
• Excel
• Power Query
• Power Pivot

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution

Preferred Qualifications

• Experience with consumer or commercial lending products such as credit cards, auto loans, personal loans, mortgages, or commercial loans
• Experience working with large enterprise data warehouses and financial systems
• Experience building automated or self service reporting solutions for business users
• Experience leveraging Python for automation, process optimization, or advanced analytics (trend analysis, scenario analysis, or custom performance monitoring)
• Experience developing, validating, or deploying analytical or statistical models using Python, including feature engineering, model evaluation, and performance monitoring in a financial or risk analytics context
• Experience supporting senior leadership with executive level reporting and insights
• Familiarity with banking regulatory and risk frameworks such as CECL, stress testing, portfolio monitoring, and audit support
• Demonstrated ability to mentor junior analysts and establish analytics best practices