Credit Risk Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Credit Risk Data Scientist II based in United States.

• Oversee the development, validation, and performance monitoring of credit risk models used for credit decisioning, risk management, loss forecasting, and regulatory reporting.
• Apply advanced statistical, econometric, machine learning, and data science techniques to credit risk modeling and forecasting challenges.
• Support and oversee models based on Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) frameworks.
• Manage and strengthen the model governance framework.
• Evaluate model performance through back testing, monitoring, validation, and adjustment activities.
• Support CECL processes.
• Contribute to stress testing, credit loss forecasting, and macroeconomic scenario analysis.
• Ensure model inputs and outputs meet appropriate standards for data integrity, data quality, and reliability.
• Develop and implement policies, procedures, and monitoring practices for credit risk model validation and oversight.
• Provide oversight of credit risk models developed or operated by external partners.
• Ensure modeling and data science activities remain aligned with organizational risk appetite, strategic objectives, and regulatory expectations.
• Lead or support project planning, execution, reporting, issue resolution, and follow-up action plans.
• Communicate model performance, risks, findings, and recommendations to senior management, auditors, regulators, and other stakeholders.

• Bachelor’s degree in quantitative finance, economics, statistics, mathematics, data science, computer science, or a related quantitative discipline.
• Master’s degree in financial engineering, data science, applied mathematics, or another quantitative field is preferred.
• 7+ years of experience in credit risk modeling, model development, model validation, model risk management, forecasting, or related quantitative functions.
• Proven experience developing or overseeing Expected Loss models using PD, LGD, and EAD methodologies.
• Deep expertise in machine learning, statistical modeling, econometric methods, and data science techniques applied to credit risk and loss forecasting.
• Strong experience with credit loss forecasting for CECL, stress testing, CCAR/DFAST, or similar regulatory and risk management applications.
• Experience with CECL modeling, implementation, and production of quantitative and qualitative components.
• Strong understanding of consumer credit products.
• Familiarity with credit scorecards, origination models, and credit underwriting analytics is highly desirable.
• Experience with regulatory frameworks and requirements such as Basel III, IFRS 9, CCAR, Dodd-Frank, and related credit risk standards.
• Experience with regulatory stress testing or impairment models is preferred.
• Proficiency with analytical and statistical tools such as Python, R, SAS, SQL, or comparable modeling platforms.
• Strong understanding of data management, data integrity, and data quality considerations.
• Strong analytical and problem-solving abilities.
• Excellent communication and presentation skills.
• Strong project leadership skills.
• A collaborative, adaptable, and detail-oriented approach.

• Base salary range of $130,146–$162,682.
• Fully remote work within the United States.
• Three medical plan options.
• Health Savings Account (HSA) options.
• Flexible Spending Accounts (FSA).
• Dental and vision insurance.
• Company-paid basic life insurance.
• Short-term and long-term disability coverage.
• Supplemental hospital indemnity, accident, and critical illness insurance.
• 401(k) retirement plan with company matching.
• Generous paid time off.
• 11 paid holidays annually.