UnitedHealth Group, Optum, is seeking a Senior Data Analyst in Draper, UT with remote options. The role centers on credit analytics, building data pipelines, dashboards, and reports to inform credit risk, underwriting, and portfolio decisions. This position offers a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and a 401k contribution.
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
Responsibilities
- Act as a senior analytics partner to the Credit team, delivering data-driven insights across credit risk, portfolio performance, underwriting, and loss mitigation
- Design, 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, automate workflows, validate results, and engineer features, complementing SQL-based workflows and boosting analytical efficiency
- Create and maintain interactive Power BI dashboards and reports to deliver clear, actionable insights to Credit leadership and stakeholders
- Develop and sustain SSRS reports to support operational, regulatory, and management reporting needs, ensuring accuracy, consistency, and timeliness
- Conduct advanced Excel analysis with pivot tables, Power Query, Power Pivot, and complex formulas to support ad hoc requests and deep-dive investigations
- Analyze credit metrics including delinquency, roll rates, charge-offs, recoveries, exposure, and vintage performance to identify trends, risks, and opportunities
- Collaborate with Credit Risk, Underwriting, Finance, and Compliance to ensure reporting aligns with business rules, policies, and regulatory expectations
- Validate data integrity and reconcile results across multiple systems to ensure reporting accuracy and reliability
- Translate complex analytical findings into clear, concise insights and recommendations tailored to technical and non-technical audiences
- Support automation and process improvements to increase efficiency, scalability, and self-service analytics within the Credit organization
- Mentor junior analysts and contribute to the development of 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
- Bachelor's degree in Data Analytics, Finance, Economics, Statistics, Information Systems, or related field, or equivalent practical experience
- 5+ years of experience in data analytics, with direct experience supporting Credit, Credit Risk, or Lending teams within a bank or financial services organization
- Advanced Power BI skills, including data modeling, DAX, custom measures, and executive-ready dashboards
- Hands-on SSRS report development, maintenance, and support in a production environment
- Solid working knowledge of credit concepts such as delinquency, charge-offs, recoveries, exposure, vintages, utilization, and portfolio performance
- Advanced Python proficiency, including pandas, NumPy, and related analytical packages for data manipulation, validation, automation, and large-scale analysis; experience building reusable scripts or pipelines is highly valued
- Expert SQL proficiency, including complex joins, CTEs, subqueries, window functions, and performance-optimized queries on large datasets
- Advanced Excel skills, including pivot tables, Power Query, Power Pivot, complex formulas, and statistical or financial analysis
- 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 capacity to independently investigate issues and deliver insights
- Excellent communication skills for explaining complex data findings to technical and non-technical stakeholders
Technologies
Technologies: Python, pandas, NumPy, SQL, Power BI, SSRS, Excel, Power Query, Power Pivot, DAX
Preferred Qualifications
- Experience with consumer or commercial lending products such as credit cards, auto loans, personal loans, mortgages, or commercial loans
- Experience with large enterprise data warehouses and financial systems
- Experience building automated or self-service reporting solutions for business users
- Experience using Python for automation, process optimization, or advanced analytics (trend analysis, scenario analysis, or custom performance monitoring)
- Experience developing, validating, or deploying analytical 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 (CECL, stress testing, portfolio monitoring, audit support)
- Demonstrated ability to mentor junior analysts and establish analytics best practices
