Financial Model Risk Management Lead

Overview

This role is part of the Enterprise Risk & Internal Audit organization, which helps protect business operations and long-term success. Responsibilities include identifying, assessing, and monitoring risk across the organization, supporting internal audits and regulatory assurance, fraud prevention, and crisis planning, and maintaining strong controls and readiness for external reviews.

You will join the Model Risk Management (MRM) team as a Lead validator for Finance and Analytics models. MRM serves as a second line of defense by establishing and overseeing a model risk management framework to identify, quantify, monitor, mitigate, and report on model risk.

Responsibilities

• Perform independent challenges of financial and analytics quantitative models, including ALM, allowance/loss forecasting, loan transition models (LTM), corporate financial planning models, take-up and engagement models, and related decision-support analytics through rigorous validation and ongoing monitoring
• Lead end-to-end validation engagements on high-complexity, high-criticality models
• Identify model weaknesses, limitations, and opportunities for improvement; clearly articulate findings to technical and non-technical stakeholders
• Collaborate with model owners and stakeholders across Finance, Quantitative Research, and Growth Analytics to remediate validation findings and strengthen model governance
• Partner cross-functionally to implement and maintain the MRM framework
• Partner with Internal Audit, Internal Controls, Accounting, and Compliance to support timely resolution of audit, regulatory, and examiner requests

Requirements

• 4–6 years of professional experience in related technical areas such as model development, model validation, quantitative finance, or data analytics, with meaningful exposure to financial and/or analytics model validation
• Deep and broad knowledge of corporate finance, treasury, ALM, and/or actuarial/statistical forecasting
• Experience in credit underwriting and/or credit risk management is a plus
• Proven ability to work with scripting languages (e.g., Python) and large-scale datasets (e.g., SQL); comfort reviewing models built in Excel, Python, Databricks, or similar environments
• Experience with statistical modeling, time-series forecasting, simulation, and/or machine learning techniques as applied to finance and analytics use cases
• BS, MS, or PhD in a quantitative field such as Quantitative Finance, Financial Engineering, Mathematics, Statistics, Economics, Computer Science, or Data Science
• Detail-oriented, intellectually curious about data, models, and business context, with strong critical thinking and structured problem-solving
• Strong interpersonal and verbal/written communication skills, including the ability to influence model owners, present to senior stakeholders, and navigate cross-functional remediation

Preferred Qualifications

• Experience in credit underwriting and/or credit risk management

Compensation & Benefits

• Pay grade: M
• Equity grade: 8
• Base pay (USA):
  • CA, WA, NY, NJ, CT: $185,000 - $245,000 per year
  • All other U.S. states: $164,000 - $224,000 per year
• New hires typically come in at the start of the pay range.
• Total compensation may include equity rewards, monthly stipends for health, wellness, and tech spending, and benefits including 100% subsidized medical coverage, dental and vision for you and your dependents.
• Additional benefits highlights:
  • Health coverage at no cost (100% of premiums for employees and their dependents)
  • Monthly spending stipends for tech setup
  • Flexible time off and generous holiday calendars
  • Employee stock purchase plan (ESPP) to buy company stock at a discount

Location

Remote-first with flexibility built in. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

For positions based in San Francisco or Los Angeles: qualified applicants with arrest and conviction records are considered as required by law.