U.S. Bank Quantitative Model Analyst in EARTH CITY, Missouri
Creates, validates, tests, documents, implements, and/or oversees usage of complex statistical models. The models may cover a variety of products or services, however, all models are used as part of the financial decision making process. Specific results focus on documenting the creation and/or testing of advanced statistical models and communicating such models to stakeholders within the Bank. Deliverables include the creation of model development and/or validation documentation such as: presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code, and procedures.
Bachelor's degree in a quantitative field, and 10 or more years of experience in statistical modeling OR
Master's or PhD degree in a quantitative field, and six or more years of experience in statistical modeling
Advanced understanding of applicable laws, regulations, financial services, and regulatory trends that affect the Mortgage Banking Industry.
Strong statistical modeling background based on technical training or advanced education in a quantitative field
Considerable knowledge of various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies, using SAS, R or similar statistical package
Strong data compilation, programming skills and qualitative analysis skills
Advanced knowledgeable of quantitative and qualitative risk factors, industry risks, competition risks, and risk management approaches
Demonstrated independence, team work and leadership skills
Strong project management skills
Excellent written and verbal communication skills
Primary Location: Missouri-MO-Earth City
Shift: 1st - Daytime
Average Hours Per Week: 40
Requisition ID: 180044667
Other Locations: Minnesota-MN-Hopkins
U.S. Bank is an Equal Opportunity Employer committed to creating a diverse workforce.
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.