Senior Data Analyst - Remote
Indexed description
Primary 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
Required Qualifications
- 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.
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.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.
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