Data Science Leader
1 month ago
We are seeking a highly skilled and experienced quantitative credit risk professional to join our team at Citizens. As a Principal Data Scientist, you will play a key role in designing, developing, testing, and executing credit risk models that cover CCAR/DFAST Stress Testing, CECL (ACL), Economic Capital, BAU Loss Forecasting, and other applications.
Key Responsibilities:
- Develop and support statistical/econometric credit risk models, including probability of default (PD), recovery/loss given default (LGD), and valuation models, analyzing correlations, concentrations, rating migrations, and risk contributions.
- Collaborate with business line partners to embed and socialize these models, providing ongoing support and requests.
- Work with the independent model validation team to obtain model approval after development is complete.
- Analyze consumer lending portfolio trends to support portfolio strategies and applications.
- Draw from source systems and maintain large data sets using advanced statistical/modeling tools, resolving or remedying data quality issues as needed.
- Maintain, review, and adhere to the organization's credit policy, verifying the integrity of underlying data and constantly monitoring and validating underlying theories and methodologies.
- Support the implementation of model development, including third-party vendor solution tools for credit risk.
- Prepare ad-hoc risk quantification projects at the request of management.
- Participate in peer review sessions and maintain awareness of new advances in credit risk modeling techniques to ensure the application of best practices to CFG credit risk models.
Requirements:
- 7+ years of experience in the financial industry working with model development.
- Prior experience in loss forecasting model development in consumer or commercial lending portfolios (consumer preferred).
- Strong understanding of commercial banking and lending products.
- Strong knowledge of statistical software packages, including SAS, Stata, R, and Python.
- Background and knowledge of the FASB CECL, DFAST rules, and other banking regulations like the Fair Lending Act.
- Understanding of compliance and implications of FDIC, OCC, FRB regulatory frameworks as well as accounting standards.
Education:
- BA Degree in a quantitative field (Econometrics, Statistics, Mathematics, Operational Research, Physics) required.
- PhD or Master's degree preferred.
Work Schedule:
- Hybrid in Boston MA Office 3 days a week, 2 remote.
- Hours per Week: 40.
- Work Schedule: Monday-Friday.
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