Manager, Model Risk and Governance

- Lead, grow, and develop a team of 3+, with real room to scale as the business does.

- Own the fundamentals and raise the bar on how we execute them: performance monitoring, drift monitoring, fair lending assessments, governance documentation, validation, model inventory, and change management.

- Set the strategy for the function. Decide what we automate, what we standardize, and where we need to be better than the industry norm.

- Own relationships for anything governance-related, across Data Science, Engineering, Partner Success, and Sales.

- Own customer relationships directly. Run customer-facing calls, work with model risk teams at banks and fintechs, and get ahead of the relationships that matter most.

- Guide customers on pushing adoption forward while meeting their governance standards. You'll often be the one who unblocks a deal or a deployment.

- Prepare validation reports, governance documentation, and performance summaries for internal leadership, customers, auditors, and regulators

- Track governance findings through remediation and manage the team's roadmap, balancing strategic work against customer and regulatory demands

- Do the work yourself when it's warranted, to move something forward or to mentor the team.

This is a high-leverage role. Governance gates how quickly our customers can adopt what we build, which makes it a direct lever on the company's growth, with substantial room for the right person to define it and grow with it.

- 8+ years in model risk management, model validation, model governance, or quantitative risk, including proven experience building or scaling a governance/risk team (not just operating within one)

- 4+ years of people management experience with proven experience building and scaling model risk or governance teams, not just operating within one

- Deep knowledge of model governance for financial institutions. You know SR 11-7, SR 26-2, OCC guidance, fair lending, and the regulatory landscape, and you have firsthand experience validating or governing ML/statistical models in a regulated environment

- Genuine technical depth: able to read the model, interrogate the methodology, and hold your own with data scientists. Working knowledge of Python and proficiency in SQL

- A strong bias for action. You balance governance rigor against speed with judgment rather than defaulting to either.

- Strong analytical skills (Excel/Google Sheets) and excellent written/verbal communication, comfortable translating technical findings for both technical and non-technical audiences

- Bachelor's degree in a quantitative field (Math, Statistics, CS, Engineering, Economics, or related STEM)

- Must be legally authorized to work in and reside in the US

- Experience working with fraud, identity verification, credit risk, or financial risk models

- Experience supporting model governance with banks or regulated financial institutions

- Experience with AWS (S3, SageMaker) and GitHub

- Master's degree in a quantitative field

$210,000-$240,000/year + equity + benefits

- Employer paid group health insurance for you and your dependents

- 401(k) plan with employer match (or equivalent for non US-based roles)

- Flexible paid time off

- Regular company-wide in-person events

- Home office stipend, and more!

- Follow Through

- Deep Understanding

- Whatever It Takes

- Do Something Smart