Credit Model Development Quantitative Lead - Small Business Portfolio; Hybrid
Wilmington, New Castle County, Delaware, 19894, USA
Listed on 2026-01-12
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Finance & Banking
Data Scientist
Work Arrangement/
Location:
This is a hybrid position requiring in-office work three days every week. Ideally the position will be based in Buffalo, NY but may be in an M&T office in Buffalo, NY, Baltimore, MD, Wilmington, DE, or Washington, DC. There is potential for a remote work arrangement if the final candidate is not near one of the above locations.
The credit model development team is looking for a senior model developer who can serve as a lead to independently develop and maintain quantitative models used for credit risk, capital planning, or underwriting. The lead may supervise the work of model development analysts and provide direction to less experienced personnel on a project-by-project basis. This is a great opportunity to be part of a highly dedicated quantitative team of model developers.
PrimaryResponsibilities
- Develop and/or lead the development of quantitative models used for credit risk, capital planning, or underwriting. This includes CCAR and CECL models and underwriting scorecards.
- Lead less experienced model developers and analysts as required to meet project objectives.
- Use Python, SAS and SQL to manipulate customer loan or financial data for statistical analysis and model development.
- Employ common model methodologies such as logistic regression, time series, survival analysis, as well as machine learning methods to create robust and flexible solutions to complex business problems.
- Work with multiple model stakeholders across different areas of the bank to create solutions to meet business needs. Use a full array of communication skills and visual analytics to comprehend and scope business partner requirements, present analyses, explain complex models to non-technical partners, and respond to enquiries from stakeholders.
- Write comprehensive and easily readable model documentation to enable Model Risk Management and stakeholders to review all aspects of model development, including justification of model methodologies chosen, candidate models, and model performance.
- Conduct business in compliance with regulatory guidance including SR 10-1, SR 10-6, SR 11-7, Enhanced Prudential Standards, etc. Adhere to applicable compliance/operational/model risk controls and other standards, policies, and procedures.
- Complete other related duties as assigned.
The position is focused on data science, data wrangling, model development and associated analyses. This includes supporting production models with performance monitoring and analyses to address stakeholder queries. As a team lead, there is an emphasis on leading projects and supervising less experienced analysts/developers on a project-by-project basis. Communication is also emphasized due to the collaborative nature of the work, including engaging multiple stakeholders from across many departments to understand their requirements, the relevant business background, and to obtain buy-in for key decision points throughout the development process and the final model.
Education and Experience Required- Proven experience managing and analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
- Bachelor’s degree and a minimum of 4 years’ proven quantitative behavioral modeling experience, or in lieu of a degree, a combined minimum of 8 years’ higher education and/or work experience, including a minimum of 4 years’ proven quantitative model development experience.
- Minimum of 4 years’ on-the-job experience with pertinent statistical software packages;
Experience in Python required. - Minimum of 4 years’ on-the-job experience with data management environment, such as SQL Server Management Studio
- Credit model development experience required.
- Experience with Logistic Regression models is required
- Financial services/banking industry experience required.
- Master of Science or Doctorate degree in statistics, computer science, engineering, economics, finance or related fields.
- Expertise in Python, SAS and SQL; experience rewriting SAS into Python is ideal.
- Credit model development experience in financial services, notably for…
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