Director, Model Risk Management
3 weeks ago
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Who we are:
Shape a brighter financial future with us. Together with our members, we're changing the way people think about and interact with personal finance. We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
SoFi's Director -- Model Risk Management is a leadership position within SoFi's second line of defense Model Risk Management organization. This role will report to the Senior Director over Model Risk Management and will lead a team conducting independent validation work on a wide variety of models. This is a highly visible role within SoFi's analytical community.
What you'll do:
- Supervise a team of 4+ model validation experts in the work of validating models to OCC 2011-12/SR 11-7 standards.
- Conduct some model validation work directly.
- Work with the Sr. Director of Model Risk Management to continually evolve validation practices and processes.
- Present and defend results of model validation projects to model owners, model users, business unit management, auditors, and regulators.
- Foster collegial relationships with model owners and users, while maintaining necessary independence from model development work.
- Stay current with industry trends and best practices in modeling and model risk management and apply them to team's work.
What you'll need:
- 10+ years of progressive experience in model development or model risk management within midsize or large U.S. financial institutions, including at least 3 years experience conducting or supervising model validation projects.
- Bachelor's degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or a quantitative field required. Master's or Ph.D. degree preferred.
- Deep knowledge of traditional statistical modeling methods (OLS, logistic regression, survival modeling, etc.) and at least moderate knowledge of artificial intelligence/machine learning approaches (gradient boosting models, neural networks, etc.)
- High attention to detail.
- Ability to explain risks associated with complex technical matters to a non-technical audience.
- Very strong written communication ability. Must be able to review the written reports of other validators for both technical content and readability.
- Experience in building and leading high-performing teams, including attracting and retaining top talent.
- Ability and confidence to exercise influence over a wide range of individuals at all levels of technical and business leadership.
- Strong programming skills in Python or R.
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