Commercial Risk Model Development Associate

santander; Stamford (CT); On-site; USD 120,000 - 180,000; Full time

Job summary

Santander is seeking a Commercial Risk Model Development Associate in Stamford, CT to support development and enhancement of quantitative risk models for commercial lending. You will work with risk, credit, data, and technology partners to translate business needs into scalable analytics and governance processes.

Applicants should have 5+ years in risk modeling, strong Python/SQL skills, and experience with large datasets; a Bachelor's is required and a Master's preferred.

Qualifications

• Bachelor’s degree in a related field or equivalent demonstrated through work experience.
• Master’s degree preferred to support advanced analytics and modeling.

Responsibilities

• Develop, implement, and monitor quantitative risk models.
• Perform data analysis, data engineering, and statistical modeling for risk assessment.
• Evaluate model performance through back-testing and benchmarking.
• Collaborate with risk, credit, data, and technology teams to deliver scalable analytical solutions.
• Support governance, validation, and documentation through the model lifecycle.

Skills

Data analysis

Statistical modeling

Risk modeling

Back-testing

Education

Bachelor's Degree in related field

Master's Degree in related field (Preferred)

Tools

Python

SQL

Job description

Commercial Risk Model Development Associate

Country: United States of America

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.

The Difference You Make:

The Quantitative Risk Modeling team is responsible for the development, implementation, monitoring, and governance of quantitative credit risk models that support Santander’s commercial lending portfolios. The team partners closely with Risk, Credit, Business Line, Data, Technology, and Model Risk Management stakeholders to enhance the bank’s risk assessment framework, improve portfolio management, and meet regulatory expectations.

Position Summary

The Associate, Risk Modeling is responsible for supporting the development, implementation, monitoring, and enhancement of quantitative risk models that inform credit risk assessment, portfolio management, allowance methodologies, and strategic decision‑making.

• Develops, enhances, implements, and monitors quantitative risk models and analytical frameworks.
• Performs data analysis, data engineering, and statistical modeling to support risk measurement and credit decisioning.
• Evaluates model performance and stability through ongoing monitoring, back‑testing, sensitivity analysis, and benchmarking.
• Identifies opportunities to improve model methodologies, predictive performance, and operational efficiency.
• Partners with business, credit, risk, and technology stakeholders to translate business requirements into scalable analytical solutions.
• Supports model documentation, testing, implementation, and governance processes throughout the model lifecycle.
• Contributes to the development of innovative risk analytics capabilities leveraging emerging technologies, automation, and advanced data techniques.

What You Bring:

• The Associate, Risk Modeling is responsible for supporting the development, implementation, monitoring, and enhancement of quantitative risk models that inform credit risk assessment, portfolio management, allowance methodologies, and strategic decision‑making.
• Develops, enhances, implements, and monitors quantitative risk models and analytical frameworks.
• Performs data analysis, data engineering, and statistical modeling to support risk measurement and credit decisioning.
• Evaluates model performance and stability through ongoing monitoring, back‑testing, sensitivity analysis, and benchmarking.
• Identifies opportunities to improve model methodologies, predictive performance, and operational efficiency.
• Partners with business, credit, risk, and technology stakeholders to translate business requirements into scalable analytical solutions.
• Supports model documentation, testing, implementation, and governance processes throughout the model lifecycle.
• Contributes to the development of innovative risk analytics capabilities leveraging emerging technologies, automation, and advanced data techniques.

Education

• Bachelor's Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Required.
• Master's Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Preferred.

Professional Experience

• 5+ Years Risk Management, Risk Modeling, AML - Required.
• Experience programming in Python, SQL, or similar analytical tools - Required.
• Experience developing, implementing, monitoring, or validating quantitative risk models in a regulated financial institution - Required.
• Experience working with large-scale financial, credit, and portfolio datasets and addressing data quality and data lineage challenges. - Required.
• Experience in commercial credit risk, risk rating models, probability of default (PD) modeling, loan risk assessment, or related credit risk disciplines - Preferred.
• Experience working with data platforms a