Note: The job is a remote job and is open to candidates in USA. Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The Senior Data Analyst will serve as a senior analytics partner to the Credit team, providing data-driven insights and supporting various analytical tasks related to credit risk and portfolio performance.
Responsibilities
- Serve as a senior analytics partner to the Credit team, providing 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
- Leverage Python (e.g., pandas, NumPy) to perform advanced data analysis, automation, validation, and feature engineering, complementing SQL-based workflows and improving analytical efficiency
- Design, build, and support interactive dashboards and reports in Power BI to deliver clear, actionable insights to Credit leadership and business stakeholders
- Create and maintain SSRS reports to support operational, regulatory, and management reporting needs, ensuring accuracy, consistency, and timeliness
- Perform advanced analysis using Excel, including pivot tables, Power Query, Power Pivot, and complex formulas, to support ad hoc requests and deep-dive investigations
- Analyze credit metrics such as delinquency, roll rates, charge-offs, recoveries, exposure, and vintage performance to identify trends, risks, and opportunities
- Partner closely with Credit Risk, Underwriting, Finance, and Compliance teams 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 both 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
Skills
- 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 hands-on experience using libraries such as pandas, NumPy, and related analytical packages for data manipulation, validation, automation, and large-scale analysis; experience building reusable scripts, analytical frameworks, or pipelines is highly valued
- Expert-level proficiency in SQL, with experience writing complex joins, CTEs, subqueries, window functions, and performance-optimized queries against large datasets
- Advanced experience with Power BI, including data modeling, DAX, custom measures, and designing executive-ready dashboards
- Advanced Excel skills, including pivot tables, Power Query, Power Pivot, complex formulas, and 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
- Solid analytical and problem-solving skills, with the ability to independently investigate issues and deliver insights
- Excellent communication skills with the ability to explain complex data findings to both technical and non-technical stakeholders
- Experience working with consumer or commercial lending products (e.g., 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 (e.g., 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 (e.g., CECL, stress testing, portfolio monitoring, audit support)
- Demonstrated ability to mentor junior analysts and establish analytics best practices
- All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution (all benefits are subject to eligibility requirements)
Company Overview