Credit Risk Data Scientist II
New
J
JobgetherConsumer credit risk
Fully remote work within the United States.Full-TimeMiddle
Salary130,146 - 162,682 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 7+ years of experience in credit risk modeling, model development, model validation, model risk management, forecasting, or related quantitative functions.
- Required Skills
- PythonSQLMachine Learning
Requirements
- Hold a bachelor’s degree in quantitative finance, economics, statistics, mathematics, data science, computer science, or a related quantitative discipline.
- Have 7+ years of experience in credit risk modeling, model development, model validation, model risk management, forecasting, or related quantitative functions.
- Bring experience developing or overseeing Expected Loss models using PD, LGD, and EAD methodologies.
- Have expertise in machine learning, statistical modeling, econometric methods, and data science techniques applied to credit risk and loss forecasting.
- Have experience with credit loss forecasting for CECL, stress testing, CCAR/DFAST, or similar regulatory and risk management applications.
- Have experience with CECL modeling, implementation, and production of quantitative and qualitative components.
- Understand consumer credit products, including credit cards, personal loans, and unsecured lending.
- Have experience with regulatory frameworks such as Basel III, IFRS 9, CCAR, and Dodd-Frank.
- Be proficient with Python, R, SAS, SQL, or comparable modeling platforms.
- Understand data management, data integrity, and data quality considerations affecting model inputs and outputs.
- A master’s degree in financial engineering, data science, applied mathematics, or another quantitative field is preferred.
Responsibilities
- Oversee development, validation, and performance monitoring of credit risk models used for credit decisioning, risk management, loss forecasting, and regulatory reporting.
- Apply statistical, econometric, machine learning, and data science techniques to credit risk modeling and forecasting.
- Support and oversee models based on Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) frameworks.
- Manage model governance controls across development, production, validation, and ongoing monitoring.
- Evaluate model performance through back testing, monitoring, validation, and adjustment, and recommend remediation.
- Support CECL modeling, implementation, production, and ongoing performance assessment.
- Contribute to stress testing, credit loss forecasting, and macroeconomic scenario analysis.
- Ensure model inputs and outputs meet data integrity, quality, and reliability standards.
- Communicate model performance, risks, findings, and recommendations to senior management, auditors, regulators, and other stakeholders.
View Full Description & ApplyYou'll be redirected to the employer's site
