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
• Strong written and verbal communication skills