Model Validation Associate – Liquidity and Market Risk

It Starts Here:

Santander is a global leader and innovator in the financial services industry and is evolving from a high-impact brand into a technology-driven organization. Our people are at the heart of this journey and together, we are driving a customer‑centric transformation that values bold thinking, innovation, and the courage to challenge what’s possible. This is more than a strategic shift. It’s a chance for driven professionals to grow, learn, and make a real difference.

If you are interested in exploring the possibilities We Want to Talk to You!

As a Sr Associate, Risk Modeling, you play a critical role in strengthening the Company’s model risk management program by ensuring quantitative models are conceptually sound, well‑governed, and aligned with regulatory expectations and industry best practices. You contribute expert insight into market conditions, emerging risks, and future trends while promoting a strong risk culture and helping the organization proactively identify, manage, and mitigate model risk across the enterprise.

• Lead and execute model risk management activities and projects in alignment with the Enterprise MRM framework, regulatory guidance, and industry best practices.

• Develop and enhance methodologies, tools, and approaches for identifying, assessing, and managing model risk across interest rate, liquidity, credit, and market risk models.

• Evaluate model conceptual soundness, key assumptions, data integrity, and overall design to ensure models are fit for purpose.

• Perform independent testing of models, including numerical, statistical, and computational accuracy, outcomes analysis, and review of governance and control processes.

• Proactively identify gaps, weaknesses, or emerging concerns in existing processes, policies, procedures, and frameworks, and support timely remediation.

• Monitor model‑related activities to minimize the Company’s exposure to model risk through quantitative analysis, risk identification, and remediation efforts.

• Communicate complex risk modeling topics, findings, and recommendations to senior management to improve decision‑making, efficiency, and risk reduction.

• Support regulatory compliance and the Company’s reputation by ensuring adherence to legal, regulatory, and internal standards related to model risk management.

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s Degree in Mathematics, Physics, Statistics, or a related quantitative field, or equivalent work experience – Required.

• Master’s Degree in Mathematics, Physics, Statistics, or a related quantitative field – Preferred.

• 7+ years of experience in model risk management covering Interest Rate Risk, Liquidity Risk, Credit Risk, and/or Market Risk – Required.

• Hands‑on experience assessing and validating term structure models, prepayment models, credit loss models, Market Risk Rule models, and ALM frameworks – Required.

• Demonstrated experience with stress testing methodologies and practices – Required.

• Strong understanding of front‑to‑back risk management processes, including risk identification, assessment, mitigation, governance, monitoring, testing, and capital calculation – Required.

• Working knowledge of the banking regulatory environment and its impact on risk management practices – Required.

• Proven ability to lead complex, cross‑functional projects related to quantitative risk modeling – Required.

• Experience supporting regulatory examinations, audits, or model risk remediation initiatives.

• Exposure to emerging risk trends and evolving regulatory expectations within financial services.

• Advanced quantitative analysis and practical modeling expertise.

• Proficiency in Python, SAS, R, and MATLAB.

• Strong knowledge of interest rate, liquidity, credit, and market risk modeling techniques.

• Model validation, outcomes analysis, and control assessment…