Manager of Model Validation in Charlotte, North Carolina
THE TEAM YOU WILL BE JOINING:
Top 25 U.S. digital financial services company committed to developing award-winning technology and services.
Named one of the top three fastest-growing banking brands in the U.S. in 2020.
Offers a full suite of products including mortgage lending, personal lending, and a variety of deposit and other banking products (savings, money-market, and checking accounts, certificates of deposit (CDs), and individual retirement accounts (IRAs)), self-directed and investment-advisory services, and capital for equity sponsors and middle-market companies.
Where permitted by applicable law, must have received or be willing to receive the COVID-19 vaccine by date of hire to be considered.
WHAT THEY OFFER YOU:
Fast paced, highly collaborative, teamwork-oriented environment
Make an immediate impact in this high visibility role
Base salary of $150-165k with bonus potential and excellent benefits package
Top-notch leadership committed to developing people
WHAT YOU WILL DO
Effectively challenge the model development process, conceptual soundness, model performance, implementation, and appropriateness of model use during validation and AR with on time delivery of high-quality work products
Effectively coach, mentor and motivate teammates and foster teamwork and a cross learning culture
Identify opportunities to enhance validation and AR processes
Engage in R&D work for alternative modeling techniques
Clearly communicate and document findings to internal and external stakeholders in a collaborative manner
Develop and maintain effective partnerships with participants / stakeholders within our model risk management community
HOW YOU ARE QUALIFIED:
7+ years model development or validation experience specific to market, credit and/or operational risk measurement methodologies and quantitative analytics
Master's or Ph.D. degree in computer science, mathematics, finance, economics, statistics or related field, or sufficient work experience and professional certificate
Ability to assess model conceptual design, back-testing of model results, theoretical underpinnings and assumptions, model owner controls over data flows, model execution, and compliance of model results with intended application by model users
Proficient in programming languages including SAS, R, Python; knowledge of Cloud model implementation is a plus