Financial Model Risk Management Lead

Overview

This role supports Enterprise Risk & Internal Audit through independent validation of financial and analytics quantitative models. Responsibilities include identifying, assessing, and monitoring model risk across Finance and Analytics, leading validation engagements for high-complexity/high-criticality models, and partnering with stakeholders to remediate findings and strengthen model governance.

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
  • related decision-support analytics
• Conduct rigorous validation and ongoing monitoring of models
• Lead end-to-end validation engagements for high-complexity, high-criticality models
• Identify model weaknesses, limitations, and opportunities for improvement; communicate findings clearly 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 organization’s model risk management (MRM) framework
• Coordinate 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 with strong critical thinking and structured problem-solving skills
• Excellent 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 range (USA, CA/WA/NY/NJ/CT): $185,000 - $245,000 per year
• Base pay range (USA, all other U.S. states): $164,000 - $224,000 per year
• New hires typically start at the beginning 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 for employees and dependents.
• Employee stock purchase plan (ESPP) allows employees to buy company stock at a discount.
• Health coverage at no cost: 100% of premiums for employees and dependents.
• Monthly spending stipends for tech setup, and the ability to choose health and wellness options.
• Flexible time off and generous holiday calendars.

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.

Additional Information

The organization is committed to providing an inclusive interview process, including accommodations for candidates with disabilities.