Credit Risk Modeling Senior Analyst - Remote

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.

The Credit Risk Modeling Senior Analyst will play a key role in developing, enhancing, and maintaining quantitative credit risk models used for Current Expected Credit Losses (CECL), stress testing, and portfolio risk assessment. This role supports both commercial and retail lending portfolios and partners closely with Risk Management, Finance, and Data teams to ensure high quality, analytically sound estimates of expected and stressed credit losses.

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.

Primary Responsibilities:

• Assist in the design, validation, and maintenance of models to support the Current Expected Credit Losses (CECL) framework, ensuring compliance with regulatory requirements
• Assist in the design and execution of enterprise and regulatory stress testing methodologies (e.g., macroeconomic scenario expansion, loss forecasting, sensitivity analysis)
• Support external and internal audit and model risk management inquiries for model related documentation
• Conduct quantitative analysis as it applies to key business areas or specific types of models
• Document models, assumptions, and methodologies in accordance with model governance and audit requirements
• Effectively challenge the Bank's models as requested, including conceptual soundness, assumptions, and appropriateness of model methodology
• Collaborate with business groups to assist in developing effective modeling approaches to accurately represent the risks for practical business use
• Identify and address potential process gaps or process improvements including data model requirement, structure and use, data governance, policy governance and other quantitative tools
• Perform other assignments and special project analysis as requested by management

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• Bachelor's degree in Statistics, Applied Mathematics, Economics, Finance, Data Science, or a related quantitative discipline
• 2+ years of hands-on experience developing, implementing, or validating credit risk models, including CECL, credit loss forecasting, regulatory stress testing, scorecard models, or early warning/behavioral risk models
• 2+ years of programming experience using Python or SAS, with demonstrated ability to perform data manipulation, model development, model performance monitoring, and statistical analysis

Preferred Qualifications:

• Experience with CECL model development, implementation, or execution experience for Commercial Real Estate (CRE) and consumer lending portfolios
• Proven solid knowledge of credit risk principles which inform credit loss forecasting
• Ability to work in a fast-paced environment, manage competing priorities and to collaborate across the organization
• Proven attention to detail and ensure data accuracy, reconciling and loading data
• Ability to problem-solve effectively independently
• Ability to communicate complex analytical issues in understandable terms appropriate for internal and external stakeholders

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $72,800 to $130,000 annually based on full-time employment. We comply with all minimum wage laws as applicable.

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.