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    Sr. Quantitative Model Validation Analyst - Minneapolis, United States - U.S. Bank

    U.S. Bank
    U.S. Bank Minneapolis, United States

    4 weeks ago

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    Description

    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

    This position is an individual contributor role residing within the Bank's Second Line of Defense Risk Management and Compliance organization. Specifically, this position supports the Model Risk Management ("MRM") program at the Bank. The overall MRM program is designed to provide governance and control to manage financial models and associated risks that may impact the company, including financial, liquidity, market, operational, reputational, strategic, and other risks as appropriate.

    Validation Analysts within MRM provide independent validation of models that the Bank relies on for making financial decisions. A robust and comprehensive model validation includes steps that independently challenge a model's conceptual framework and methodology, data used in the model, implementation process, as well as model usage and performance. The validation process also identifies corrective actions to ensure timely remediation of model risk.

    The individual in this position works with Model Owners and Developers to validate models related to Cybersecurity, adhering to OCC Regulatory Guidance and USB's Model Risk Management Policy and Standards. The Analyst will be responsible for documenting and presenting the model validation findings to Model Owners/Developers, as well as interface with key stakeholders, regulators (OCC/FRB), and internal auditors to discuss these reported observations and published outcomes.

    Necessary Skills

    • Demonstrated ability to work independently as well as across collaborative groups.
    • Strong project management skills.
    • Has considerable knowledge of various machine learning algorithms and their applications, including (but not limited to): Random Forest, GBM, XGBoost, deep learning, NLP, and ensemble methods.
    • Able to perform complex mathematical analyses utilizing various statistical methods or techniques including cluster analysis, KNN, outlier methods and other ensemble techniques.
    • Can independently assess, test, document, and oversee the usage of advanced quantitative methods. Deliverables will include the creation of validation documentation such as: presentations, written reports, validation benchmarks models and support for identified concerns and proposed enhancements.
    • Proficiency in Python, and experience with deep learning frameworks such as PyTorch, Tensorflow/Keras, MXNet.
    • Can retrieve, analyze and interpret data from various data sources (internal and external).
    • Can aggregate and/or create datasets from different databases (structured or non-structured) to facilitate analyses related to model development or validation.
    • Able to design and perform ad hoc analyses using standard or advanced exploratory data analysis (EDA) techniques.
    • Can interpret results from analyses performed and communicate outcomes to senior executive level management in written and/or verbal form.
    • Can prepare and communicate analysis and outcome for presentation to audit and regulatory examiners.
    • Able to read, understand, and interpret regulatory rules and guidance related to the model(s) being assessed.
    • Ability to understand the business product or structure to ensure models capture the core elements and risks of interest.
    • Ability to build strong relationships with stakeholders, business line partners, and colleagues across the Bank.
    Basic Qualifications
    - Bachelor's degree in a quantitative field, and eight or more years of relevant experience
    OR
    - MA/MS in a quantitative field, and five or more years of related experience
    OR
    - PhD in a quantitative field, and four or more years of related experience

    Preferred Skills/Experience
    • Direct experience in the development and testing of machine learning models. This work could be in the form of research experience at a university or industry lab, with primary emphasis on application of complex modeling methods. Experience and authored research publications in machine learning model training, fine-tuning, reinforcement learning, or Gen AI application development/deployment are strongly preferred.
    • Advanced understanding of applicable compliance laws, regulations, financial services, and regulatory trends in the cybersecurity space.
    • Prior exposure to validation of Machine Learning and NLP models.
    • Prior experience working with a Financial Institution.
    • Deep understanding of modeling methods for extreme imbalanced data.
    • Experience using Python is required; experience using SAS, STATA, R, EVIEWS, or comparable statistical software or languages (e.g., SQL) is also desirable.
    • Strong people leadership skills.
    NOTE: This role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.

    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.

    The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. 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). Pay Range: $116, $136, $150,480.00

    U.S. Bank will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance.

    Job postings typically remain open for approximately 20 days of the posting date listed above, however the job posting may be closed earlier should it be determined the position is no longer required due to business need. Job postings in areas with a high volume of applicants, such as customer service, contact center, and Financial Crimes investigations, remain open for approximately 5 days of the posting listed date.
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