* 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.
Overview:
The credit model development team is looking for a senior model developer that 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.
Primary Responsibilities:
- 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, boosted trees and similar 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 that meet their business needs. Use a full array of communication skills and visual analytics to obtain 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, model performance.
- Conduct business in compliance with regulatory guidance including SR (Supervision and Regulation Letters) 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.
Scope of Responsibilities:
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 behavioral modeling experience
- Minimum of 4 years’ on-the-job experience with pertinent statistical software packages; experience in SAS required.
- Minimum of 4 years’ on-the-job experience with data management environment, such as SQL Server Management Studio
- Proven experience managing and analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs.
- Model development experience.
- Financial services/banking industry experience required.
Education and Experience Preferred:
- Masters’ 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.
- Model development experience in financial services, notably for common methodologies such as logistic regression, time series, survival analysis, boosted trees and similar machine learning methods.
- Experience with the development of underwriting scorecards and/or CCAR/CECL models is greatly valued.
- Logistical regression is highly preferred.
- PD & LGD models experience
- Knowledge and familiarity with key aspects of model risk management and model validation, including SR-11-7 guidance on model risk management
- Proven track record for being able to work autonomously and within a team environment
- Strong desire to learn and contribute to a group
- Previous experience leading and directing the work of less experienced personnel
Location
Clanton, Alabama, United States of AmericaOriginally posted on Himalayas
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