Credit Model Development Quantitative Manager (Hybrid - see potential locations in description)

Senior Model Developer

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, NYC, NY, Wilmington, DE, or Washington, DC. There is potential for a remote work arrangement, within the United States, 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 will manage a team of quantitative analysts and modelers to develop, implement, maintain, analyze and manage quantitative / econometric behavioral models used for credit risk, capital planning and / or underwriting. Assists with directing daily and long-range strategic direction of the group to support business initiatives and regulatory compliance. This is a great opportunity to be part of a highly dedicated quantitative team of model developers.

Primary Responsibilities

Lead teams in research and end-to-end development of quantitative models used for credit risk, including but not limited to, loss forecasting (loan delinquency, default and loss, loan prepayment, utilization, etc), capital planning (CCAR) CECL and / or underwriting

Utilize next gen quantitative approaches (AI / ML), programming routines and other econometric analyses to facilitate the model development effective challenge process communicate results, including graphic and tabular forms, to fellow team members, stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.

Manage satisfactory model documentation, including process narratives and performance monitoring guidelines to serve as reference source. Lead engagements with colleagues in Model Risk Management for model validation exercises.

Work with a wide range of internal customers, including executive management, to explain the benefits, limitations, assumptions and requirements for proposed models, scorecards and forecasts.

Work closely with internal and external business partners to develop and implement strategies for optimal pricing, underwriting or funding strategy with the end goal of maximizing firm profitability.

Develop and implement performance metrics, reporting and analyses using models to support data-driven decision-making and forecasting for the firm's customers, products and portfolios.

Manage knowledge of Bank-specific and industry data sources necessary to support quantitative analytical and modeling efforts. Serve as liaison across Bank-wide stakeholders to ensure appropriate data sourcing for projects.

Serve as subject matter expert for on all facets of quantitative risk management and guide junior analysts and data scientists during the model development process.

Mentor and supervise work of less experienced team members and assist in development of their technical and professional acumen.

Define, develop and deploy best risk management practices and infrastructure Bank-wide.

Exercise usual authority of a manager concerning staffing, performance appraisals, promotions, salary recommendations, performance management and terminations.

Understand and adhere to the Company's risk and regulatory standards, policies and controls in accordance with the Company's Risk Appetite. Design, implement, maintain and enhance internal controls to mitigate risk on an ongoing basis. Identify risk-related issues needing escalation to management.

Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.

Complete other related duties as assigned.

Scope of Responsibilities

This role is highly technical in nature and requires strong attention to detail, execution and follow-up on multiple initiatives within Finance. The ability to identify, analyze, rationalize and communicate complex business problems and recommend solutions is a key factor of success in this role. Success in this role requires the ability to use analytics in a collaborative effort across multiple functions and products to derive optimum solutions to business problems. This position interacts with most business and functional areas of the Bank, as well as with vendors, risk management consultants and supervisory bodies. The position also has occasional informational / educational meetings with internal and external customers. The position supervises the work and leads / manages teams of individual contributors, providing objective-setting, developmental opportunities and performance feedback as appropriate.

Education and Experience Required

Bachelor's degree in statistics, economics, finance or related field in the quantitative social, natural, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management and a minimum of 6 years' proven quantitative behavioral modeling experience (inclusive of a minimum of 2 years' supervisory, management and / or work leadership experience), or in lieu of a degree, a combined minimum of 10 years' higher education and / or work experience, including a minimum of 6 years' proven quantitative behavioral modeling experience (inclusive of a minimum of 2 years' supervisory, management and / or work leadership experience)

Proven experience managing and analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts / graphs

Strong leadership skills; manager of people & project management

Education and Experience Preferred :

Knowledge and familiarity with key aspects of model development for behavioral / quantitative models, including time series, scorecard, logistic regression, financial valuation or panel data models for credit risk, interest rate risk or liquidity risk management

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

Experience with pertinent statistical software packages (e.g. SAS, Python, Stata, R)

Experience with data management environment, such as SQL Server Management Studio

CCAR and / or CECL experience