Machine Learning Model Risk Specialist

The Team: 

Upstart’s ML Model Risk team is responsible for ensuring that the risk of machine learning (ML) models at Upstart is well-understood, monitored, and mitigated, which requires deep understanding of the models themselves. This work is essential for Upstart’s internal risk management, ensuring that our models help us make better decisions, and to maintain credibility with external stakeholders such as our lending partners and regulators. The team’s focus is on articulating sound model risk management principles and implementing them in collaboration with our peers on Upstart’s Risk and Machine Learning teams. This work also includes explaining our ML models to stakeholders, supporting external validations, and conducting analyses to reinforce our goals.

As an ML Model Risk Specialist at Upstart, you will contribute to the implementation of Upstart’s model risk management program. This work includes collaborating with our Machine Learning teams to meet model risk management requirements, with tasks ranging from producing robust model documentation, assisting with monitoring and validation efforts, and partnering with other Upstart stakeholders to understand model risk management needs across the enterprise.

How you’ll make an impact

• Partner with model developers in the Machine Learning team to maintain robust and up-to-date model inventory, model risk assessments, documentation, and monitoring reports. For instance, ensure that documentation is both technically adequate and comprehensible to stakeholders with varying needs and levels of technical sophistication.
• Partner with ML teams to provide effective challenge of Upstart’s models and communicate modeling assumptions to external stakeholders.
• Help answer model questions from lending partners, in collaboration with other teams.
• Collaborate with central Upstart’s Legal and Compliance teams as needed to ensure our model risk management  implementation meets or exceeds Upstart’s internal policies as well as regulatory requirements.
• Track team goals and progress. Perform risk assessment for the  model risk management program.

Minimum Qualifications 

• Master’s degree in quantitative field such as finance, mathematics, economics, statistics or a related discipline
• Internship or project experience related to model risk management, model governance, machine learning, or data science.
• Basic understanding of AI/ML methodologies such as tree-based models and neural networks
• Experience coding in R, Python, or similar languages such as Matlab

Preferred Qualifications

• PhD in a quantitative field of study such as statistics, econometrics, finance, mathematics; or a related discipline
• 1+ years of experience in model risk management or model governance, or related fields such as ML and Data Science, Risk, Trust and Safety, or Technical Writing
• Strong communication skills: ability to adapt technical information to varying needs and audiences, and managing trade-offs such as providing modeling detail while protecting intellectual property
• Proactive mindset with the ability to take initiative 
• Understanding of advanced AI/ML topics such as model monitoring, fairness, and explainability
• Advanced coding skills in R, Python, and SQL, and experience using Git
• Interest in or knowledge of consumer lending 

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.