IRRBB & ALM Subject Matter Expert

Title: IRRBB & ALMSubject Matter Expert

Level: Director

Location:
New York, NY (on site)

We are seeking a highly skilled Interest Rate Risk in the Banking Book (IRRBB) & Asset–Liability Management (ALM) Subject Matter Expert with deep expertise in interest rate risk measurement, behavioral modelling, balance sheet analytics, and regulatory risk management frameworks. The ideal candidate will also bring hands‑on experience designing, enhancing, or validating IRRBB quantitative models—including EVE/NII sensitivity, behavioral models (NMD, prepayments), repricing models, and stress testing tools.

This senior role will support the optimization of IRRBB governance, risk identification, measurement methodologies, risk appetite calibration, and model development. The successful candidate will sit within Treasury , and will interface with ALM execution , Risk Management, Finance, and regulators while driving analytical enhancements and ensuring compliance with global regulatory standards.

• IRRBB Strategy, Risk Measurement & Governance :
• Lead the development, enhancement, and maintenance of IRRBB measurement methodologies, including EVE, NII, NIM sensitivity and IRRBB stress testing frameworks.
• Ensure alignment of IRRBB practices with Basel /US standards, regulatory expectations, and industry best practices.
• Manage and continuously improve behavioral assumptions for non - maturity deposits (NMDs), loan prepayments, early redemptions, and product optionality.
• Support the design and calibration of risk appetite metrics, limits, monitoring processes, and escalation protocols.
• Partner with Treasury and senior management to assess interest rate exposures and recommend hedging or balance sheet strategies.
• Model Development, Enhancement & Validation :
• Develop, implement, or enhance IRRBB quantitative models, including: NMD behavioral models;
  Prepayment/early redemption models;
  Repricing and yield curve models;
  Dynamic balance sheet simulations;
  Replication portfolio methodologies.
• Lead or support model documentation, performance monitoring, back testing , and benchmarking.
• Collaborate with Model Validation to address findings, strengthen model robustness, and ensure end-to-end model lifecycle compliance.
• ALM Analytics & Balance Sheet Insights :
• Perform advanced ALM analytics to support Treasury’s strategic decision making .
• Deliver insights on hedging strategies, balance sheet duration positioning, and interest rate scenarios.
• Partner with Liquidity Risk, Capital Management, and Finance to assess interactions between IRRBB, liquidity, capital ratios, and earnings forecasts.
• Stakeholder Collaboration & Regulatory Engagement :
• Collaborate closely with Treasury, Market Risk, Finance, FTP, and IT to ensure consistent IRRBB frameworks and data integrity.
• Serve as a key point of contact during regulatory exams, audits, and internal risk reviews.
• Communicate model results, methodologies, and risk insights to senior management and committees.
• Data, Systems & Technology :
• Support enhancements to ALM/IRRBB systems (Risk engines, ALM platforms, FTP engines).
• Drive improvements in data quality, scenario management, and reporting automation.
• Work with quantitative and technology teams to implement new models and analytics into production environments.

• Education:
• Bachelor's or Master's degree in Economics, Mathematics, Statistics, Data Science, Engineering, or related fields.
• Professional certifications such as CFA, FRM, PRM are highly beneficial.
• Experience:
• Minimum 7–10+ years of experience in IRRBB, ALM, Market Risk, Treasury Risk, or related quantitative functions.
• Hands on experience developing, enhancing, or validating IRRBB models (EVE/NII, NMD, prepayment).
• Strong familiarity with US & Basel IRRBB Standards, US regulatory expectations, and industry practices.
• Experience with ALM platforms or quantitative risk engines (e.g., QRM, Empyrean, Moody’s, Kamakura, Banc Ware , internal models).
• Technical
  
  Skills:
  
  
• Strong quantitative and statistical background.
• Proficiency in Python, R, or similar languages is strongly preferred.
• Solid understanding of interest rate modelling concepts (e.g., term…