Senior Data Analyst - Remote

UnitedHealth Group•Draper, UT

8h•Remote

About The Position

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. 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.

Requirements

Bachelor’s degree in Data Analytics, Finance, Economics, Statistics, Information Systems, or a 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 experience with Power BI, including data modeling, DAX, custom measures, and designing executive-ready dashboards
Hands-on experience developing, maintaining, and supporting SSRS reports in a production environment
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
Proven advanced Excel skills, including pivot tables, Power Query, Power Pivot, complex formulas, and statistical or financial analysis
Proven ability to validate data, reconcile across multiple source systems, and ensure high data quality and reporting accuracy
Proven solid analytical and problem-solving skills, with the ability to independently investigate issues and deliver insights
Proven excellent communication skills with the ability to explain complex data findings to both technical and non-technical stakeholders

Nice To Haves

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

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