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Market-Observed Role 🔍 Observed Likely Active (65-79)
This role was detected through Mercury's hiring system and hasn't been verified directly by the employer. Our algorithm scored it as Likely Active (65-79) based on freshness, specificity, and company patterns. What does this mean? →

IRRBB Manager

Mercury
🔍 Observed
76
Hiring Activity Score
Likely Active (65-79)
  • Base score
  • Posted 1 days ago
  • has location, quality description (5591 chars)
  • 48 new listings in 30d (×0.98 age 1d)
  • 3 skills
  • Direct ATS (greenhouse)
How the Hiring Activity Score works →
San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States First seen 1 day, 4 hours ago Last seen 4 hours, 54 minutes ago Greenhouse
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Job Description

Role Overview

We are seeking an analytical and technically skilled professional to lead the implementation, management, and ongoing enhancement of our cash flow engine. This role will be responsible for modeling balance sheet cash flows, supporting interest rate risk (IRR) analytics, and ensuring the integrity of key metrics such as Net Interest Income (NII) and Economic Value of Equity (EVE).

The ideal candidate brings a strong understanding of asset-liability management (ALM), behavioral modeling, and financial modeling frameworks, along with the ability to translate complex assumptions into actionable insights.

Key Responsibilities

  • Support the vendor selection and system implementation of the firm’s cash flow engine / ALM system
  • Develop, maintain, and enhance cash flow models for assets and liabilities that will be used for risk monitoring and balance sheet forecasting
  • Produce and analyze interest rate risk metrics, including NII and EVE under various scenarios
  • Design, document, and support behavioral assumptions (e.g., prepayments, deposit decay, betas, non-maturity deposit modeling)
  • Partner with Finance and Risk teams to ensure alignment of modeling assumptions and outputs
  • Perform scenario analysis and sensitivity testing to support balance sheet strategy and risk management
  • Ensure data integrity, model accuracy, and compliance with internal policies and regulatory expectations
  • Support model validation, audit, and regulatory review processes
  • Identify opportunities to improve automation, efficiency, and model sophistication

Qualifications

  • Bachelor’s degree in Finance, Economics, Mathematics, Engineering, or a related field (advanced degree preferred)
  • 5+ years of experience in bank ALM, bank Treasury, IRR modeling, or quantitative finance
  • Strong understanding of:
    • Bank balance sheets, products, and cash flow drivers
    • Net Interest Income (NII) modeling
    • Economic Value of Equity (EVE)
    • Interest rate risk frameworks
    • Cash flow hedging
  • Experience developing and supporting behavioral models and assumptions (e.g., deposits, loans, prepayments)
  • Hands-on experience with ALM or cash flow engine platforms (e.g., QRM, Empyrean, BancWare, or similar)
  • Strong quantitative and analytical skills; proficiency in Excel and/or programming tools (Python, SQL, R a plus)
  • Ability to communicate complex modeling concepts to non-technical stakeholders

Preferred Skills

  • Experience in banking* or financial services
  • Familiarity with regulatory expectations for IRRBB and model risk management
  • Experience with model validation or governance frameworks
  • Strong problem-solving mindset with attention to detail

What Success Looks Like

  • A fully implemented and reliable cash flow engine supporting accurate NII and EVE projections with up to monthly production runs
  • Well-documented and defensible behavioral assumptions
  • Supporting a cross functional operating model for balance sheet forecasting
  • Clear, actionable insights that inform balance sheet and risk management decisions
  • Scalable modeling infrastructure that evolves with the business

Compensation

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

  • US employees in New York City, Seattle, Los Angeles or San Francisco: $207,800 - $259,800
  • US employees outside of New York City, Seattle, Los Angeles or San Francisco: $187,000 - $233,800
  • Canadian employees (any location): CAD  196,400 - 245,500

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.] 

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Skills

sql python go
Job Information
  • Company:
    Mercury
  • Location:
    San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
  • Job Type:
    Internship
  • Work Location:
    Remote
  • Experience Level:
    Mid
  • Source:
    Greenhouse
  • Status:
    Active
Activity Score
76 /100
Likely Active (76)

Higher scores indicate more likely active hiring based on listing freshness, company activity, and other signals. Learn more →

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