The Team

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

As a Senior Model Risk Specialist at Upstart, you will play a critical role in making robust model risk management a reality by leading day-to-day implementation of Upstart’s model risk management program. This work includes partnering 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 ML 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 understandable to stakeholders with varying needs and levels of technical sophistication.
• Partner with ML teams and external partners to conduct robust model validation.
• Answer model questions from lending partners, in collaboration with other teams.
• Partner with central Model Risk, Legal and Compliance teams as needed to ensure implementation meets or exceeds Upstart’s internal policies as well as regulatory requirements.

Minimum qualifications 

• Bachelor's degree in quantitative field such as finance, mathematics, economics, statistics or a related discipline
• 2-3 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
• 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

• Advanced degree in a quantitative field
• 2-4 years experience in similar roles
• Effective communication skills: ability to adapt technical information to varying needs and audiences, and managing trade-offs such as providing modeling detail while protecting IP
• 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
• Consumer lending knowledge and/or experience within an ML-centric technology company

Position location

This role is available in the following locations: San Mateo, California; Columbus, Ohio; Austin, Texas; or Remote USA

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.

What you'll love

• Competitive compensation (base + bonus & equity)
• Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart 
• 401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings
• Employee Stock Purchase Plan (ESPP)
• Life and disability insurance
• Generous holiday, vacation, sick and safety leave  
• Supportive parental, family care, and military leave programs
• Annual wellness, technology & ergonomic reimbursement programs
• Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering
• Catered lunches + snacks & drinks when working in offices

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