Director, Risk Analytics Models

The role

SoFi's Director of Modeling for Risk Analytics (2LOD) is a leadership role within SoFi's growing 2nd line of defense organization. This strategic role will be instrumental in implementing SoFi's member trust-oriented strategy through building a best-in-class risk modeling team.

This role will work closely with the VP Risk Analytics and provide the leads of SoFi's individual risk stripes within the 2nd line of defense with model buildout and validation, and guide measurement, strategy, and data-driven decision making. These tasks involve developing complex business rules to researching and applying state of the art machine learning modeling methodologies to solve complex business problems. This is a pivotal role for the 2nd line of defense as we execute on our mission to help more Members get their money right.

What you'll do:

• Build out the new Modeling team within the 2LOD Risk Analytics team, including developing the modeling strategy for 2nd line of defense, aligning key deliverables, and resourcing a new team.

• Work closely with the VP of Risk Analytics and other risk management leaders to develop and implement modeling strategies that align with SoFi's objectives. Provide expert guidance on model buildout, validation processes, and risk measurement techniques.

• Proactively identify opportunities to apply advanced machine learning approaches (e.g., NLP, LLM,, Graph Mining, etc) to solve complex business problems

• Explore and leverage in-house, external, and other open-source machine learning software/algorithms

• Possess deep understanding of SoFi's data and reporting capabilities and technology, including the familiarity with attribute-level data and dictionaries and data extraction, transformation and visualization tools.

• Identify synergies and efficiencies between the data models and analytics used across risk stripes to provide modeling solutions

• Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking

• Present model performance and insights to Risk and Business Unit leaders

What You'll Need

• 10+ years of progressive experience building and implementing risk models within U.S. global systemically important financial institutions' risk organizations, including 5+ years in senior leadership

• Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or quantitative field required. Master's or Ph.D. degree preferred.

• Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but not limited to) regression, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications. Continuously follow the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies

• Experience in enabling service models and delivering SLA-based services to internal stakeholders.

• Familiarity with model risk management regulatory requirements (SR 12-7)

• Ability to dive into details to generate insights and effectively communicate complex models in simple terms to audiences of all levels in the organization, including executives..

• Strong presentation skills: able to use data to tell a clear and compelling story; comfortable with public speaking across various forums including regulatory examinations and be able to effectively and logically communicate when information is being challenged in an open forum

• 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 & business leadership

• Strong programming skills in Python

• Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc.