Financial Model Risk Management Lead

Overview

This role involves joining the Model Risk Management (MRM) team within Enterprise Risk & Internal Audit as a Lead validator for Finance and Analytics models. MRM serves as a second line of defense by establishing and overseeing an effective model risk management framework to identify, quantify, monitor, mitigate, and report on model risk across 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
  • related decision-support analytics
  • Validate and continuously monitor models through ongoing validation activities
• Lead end-to-end validation engagements for high-complexity, high-criticality models
• Identify model weaknesses, limitations, and opportunities for improvement; clearly communicate 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
• Work 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 and intellectually curious about data, models, and business context; strong critical thinking and structured problem-solving
• Extraordinary 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
  • All other U.S. states: $164,000 - $224,000 per year
• Employees new to the organization typically come in at the start of the pay range.
• Base pay is 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.)
• Benefits highlights:
  • Health coverage at no cost: 100% of premiums for employees and their dependents
  • Spending stipends: monthly stipends for tech setup and the ability 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 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 will be considered, as required by law.