Financial Model Risk Management Lead

Overview

The Enterprise Risk & Internal Audit department protects the organization’s operations and long-term success by identifying, assessing, and monitoring risk across the business. Work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The function maintains controls, tracks key risk indicators, and supports readiness for external reviews.

This role joins 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 throughout the organization.

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 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 both 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 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 with strong critical thinking and structured problem-solving skills
• Extraordinary interpersonal and verbal/written communication skills, including the ability to influence model owners, present to senior stakeholders, and navigate cross-functional remediation

Compensation & Benefits

• Pay Grade: M
• Equity Grade: 8
• Base pay range (USA):
  • $185,000 – $245,000 per year (CA, WA, NY, NJ, CT)
  • $164,000 – $224,000 per year (all other U.S. states)
• Compensation includes base pay as part of a total compensation package that 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)
• New hires typically come in at the start of the pay range

Benefits highlights include:

• Health coverage at no cost: 100% of premiums for employees and their dependents
• Spending stipends: monthly stipends for tech setup and flexibility to choose health and wellness options
• Time off: flexible time off and generous holiday calendars
• Employee stock purchase plan (ESPP): buy stock at a discount

Location

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

For positions based in San Francisco or Los Angeles: the organization considers qualified applicants with arrest and conviction records, as required by law.