** Work Arrangement/Location: This is a hybrid position requiring in-office work three days every week.  Ideally the position will be based in M&T's Bridgeport, CT office but it may be in an M&T office in Buffalo, NY, Baltimore, MD, NY, NY, Paramus, NJ, Iselin, NJ, 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:

Senior developer within Treasury to support data, systems and forecasting needs of Treasury’s credit, interest rate risk, liquidity risk, CCAR (Comprehensive Capital Analysis and Review)/stress testing and economic capital practices.  Serves as Bank-wide or industry expert in key area(s) of quantitative risk management.  Provides mentoring, training, and guidance to less experienced analysts and may lead/manage teams on a project basis, providing performance feedback to management as appropriate.

Primary Responsibilities:

• Lead research and development for origination, credit, financial, demographic, behavioral, market and economic data pertinent to the Bank’s customers, portfolios and products.  Interpret results, develop recommendations, and present findings to senior management.

• Support the end-to-end model development and implementation process for behavioral models supporting the firm’s credit risk management, interest rate risk, liquidity risk, stress testing and economic capital practices.  Facilitate the model development effective challenge process with the Model Development Working and Model Development Oversight Groups.
• 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, maintain, and manage satisfactory model documentation, including process narratives and performance monitoring guidelines to serve as reference source.   
• Lead financial analysis and data support to other groups/departments across the Bank as required, serving as Bank-wide expert in area(s) of quantitative risk management. Lead engagements with colleagues in Model Risk Management for model validation exercises.
• Provide guidance and direction to less experienced personnel regarding all aspects of data and financial analysis and the development and management of predictive statistical models.
• Understand and adhere to the Company’s risk and regulatory standards, policies and controls in accordance with the Company’s Risk Appetite.  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:

The position serves as a quantitative expert in use of statistical programming languages to analyze Bank datasets and development, implementation and maintenance of credit risk models.  It is important for the position to communicate with clear narratives, compelling data visualization and technical precision, both in-person and in writing, to enable audiences to understand analysis and forecasts.  The position partners and collaborates with colleagues in related functions, including Credit Risk Management, Commercial and Consumer Business Units, Model Risk Management and review functions (Credit Review, Audit, etc.) to implement and understand models for Bank use.  The position often leads team-based projects related to model development or implementation.  This role is highly technical in nature and requires demonstrated attention to detail, execution and follow-up on multiple initiatives within Finance and across the Bank.  The ability to identify, analyze, rationalize and communicate complex business, data and statistical problems and recommend corresponding solutions while directing the work of others on the team is a key factor of success in this role.  The position may supervise the work of interns and/or lead teams on a project basis, providing performance feedback to management as appropriate.  The position also provides guidance and direction to less experienced personnel.

Education and Experience Required:

• Bachelor’s degree and a minimum of 6 years’ proven quantitative behavioral modeling 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
• Minimum of 6 years’ on-the-job experience with pertinent statistical software packages (SAS, Python, Stata, R)
• Minimum of 6 years’ on-the-job experience with data management environment, such as SQL Server Management Studio
• Minimum of 6 years’ on-the-job experience analyzing large data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
• Credit modeling experience, including commercial credit score card development

Education and Experience Preferred:

• Masters’ of Science or Doctorate degree in statistics, economics, finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
• Minimum of 8 years’ statistical analysis programming experience
• Strong Python skills
• Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) designation
• Fluency and high proficiency in econometric/statistical techniques, especially time-series analysis, panel data methods and logistic regression
• Experience in balance sheet management and mathematical modeling of financial instruments offered by banks
• 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
• Proven leadership skills
• Strong desire to learn and contribute to a group
• Previous experience leading and directing the work of less experienced personnel

Location