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Quantitative Model Analyst - Economic Sanctions & Fair and Responsible Banking (Multiple openings) in Irving, TX

U.S. Bank

U.S. Bank

IT
Irving, TX, USA
Posted on Mar 31, 2025

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

Job Description

U.S. Bank is seeking a full-time Quantitative Model Analyst - Economic Sanctions & Fair and Responsible Banking (Multiple openings) in Irving, TX.

Essential Responsibilities:

Perform validations and reviews on models in the Economic Sanctions and Fair and Responsible Banking Division areas, by carrying out analysis utilizing various statistical methods and techniques, including descriptive and inferential statistics, multivariate analysis and machine learning techniques, in order to analyze the datasets, infer meaningful descriptions and relationships between the data used and the method being validated, test the thresholds utilized by the methods and validate the overall effectiveness and soundness of the methods being reviewed to ensure they are performing as expected. Specific duties and responsibilities include:

  • Perform exploratory data analysis, using SAS and Python programs, to carry out data inspections, data cleaning, data transformations, multivariate analysis and descriptive analysis on the data used by the models being reviewed.
  • Perform independent assessment of models and tools developed internally by the Bank and externally by vendors. Internally developed models include anomaly detection models used to identify suspicious activities and logistic and regression-based models used in the Fair Lending and Responsible Banking area to assign proxies where customer reported information is unavailable. The externally developed models include the sanction screening fuzzy logic models used in the Economic Sanctions Program.
  • Perform independent testing of models and tools (programs) being reviewed, using SAS and Python programming codes to replicate the programs’ logic, analyze programs’ output and assess the effectiveness of the programs to their respective objectives.
  • Perform review of documents related to the programs being reviewed, which include development documentation, monitoring plan and reports, implementation plan and testing framework to ensure that the documents are comprehensive, accurate and follow regulatory guidelines.
  • Communicate progress of the reviews to the program owners that include results of documentation review, exploratory data analysis and independent model testing via weekly presentation and question tracker.
  • Responsible for the creation and maintenance of validation report for each independent model validated, that documents the activities of the review, results of the validation, and proposed enhancements to be carried out by the program owners.
  • Provide support to the team by participating in additional activities and reviews that include creation of provisional approvals and documentation of closures associated with recommendations of different programs.

Basic Qualifications:

This position requires a Master’s degree or equivalent in Data Science or Computer Science and 2 years data analysis experience.

Required Skills/Experience:

Must also have 12 months of experience with each of the following: 1) Performing statistical analysis on data collected from quantitative financial models. 2) Creating, validating, testing, documenting, implementing and overseeing the usage of complex statistical models that utilize approaches including logistic and linear regression, outlier detection, and fraud detection. 3) Implementing proof of concepts to detect fraudulent activities utilizing Machine Learning techniques including logistic and linear regression, decision trees, random forests, naïve bayes, light gradient boosting machine (LGBM), extreme gradient boosting (XGBoost). 4) Designing and developing automation tools that help automate and repetitive tasks to reduce manual efforts via Python programming language. 5) Delivering audit testing, including Anti Money Laundering, Transaction Monitoring, Sanctions Screening, Whistleblowing, and Fraud Machine Learning models, with the use of Analytics and Machine Learning techniques including Decision Tree, Random Forest, and Data Visualizations. Will accept experience gained before, during or after Master’s program. Employer will accept experience gained concurrently.

This position is with U.S. Bank National Association, a U.S. Bank company.

Base pay range may vary if an offer is made for work in a different location. Pay Range: $59,821 - $155,000. (#LI-NDI #LI-DNI #LI-DNP #DE-DNP).

If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants.

Benefits:

Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following (some may vary based on role, location or hours):

  • Healthcare (medical, dental, vision)

  • Basic term and optional term life insurance

  • Short-term and long-term disability

  • Pregnancy disability and parental leave

  • 401(k) and employer-funded retirement plan

  • Paid vacation (from two to five weeks depending on salary grade and tenure)

  • Up to 11 paid holiday opportunities

  • Adoption assistance

  • Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

EEO is the Law

U.S. Bank is an equal opportunity employer committed to creating a diverse workforce. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, among other factors. Applicants can learn more about the company’s status as an equal opportunity employer by viewing the federal KNOW YOUR RIGHTS EEO poster.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about the E-Verify program.

In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements).

U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures.

Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.