Credit Model Development Quantitative Lead; Hybrid

Hybrid Quantitative Behavioral Modeling Position

Independently develops, implements, maintains, analyzes and manages quantitative/econometric behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning. May supervise the work of interns and/or lead teams, providing performance feedback to management as appropriate. Provides guidance and direction to less experienced personnel.

• Lead research and development of quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning.
• Prepare, manage and analyze large customer loan, deposit, or financial data sets for statistical analysis in Structured Query Language (SQL) or similar tool.
• Run regressions, programming routines and other econometric analyses to specify models.
• Execute models in production environment; communicate analytical results to Bank-wide stakeholders.
• Develop, maintain and manage satisfactory model documentation.
• Lead financial analysis and data support to other groups/departments across the Bank.
• Provide guidance and direction to less experienced personnel regarding all aspects of data and financial analysis.
• Conduct business in compliance with regulatory guidance.
• Serve as lead in managing Treasury projects and initiatives.
• Maintain M&T internal control standards.
• Complete other related duties as assigned.

The position serves as team lead in use of statistical programming languages to analyze Bank datasets and development, implementation and maintenance of behavioral 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, Asset Liability and Liquidity Management, Model Risk Management and business lines 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 Treasury 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 of up to three individual contributors, providing performance feedback to management as appropriate. The position also provides guidance and direction to less experienced personnel.

• 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.
• Fluent in at least one open-source language for development: R, Python.
• Experience in end-to-end model development lifecycle.
• Experience working directly with model users and stakeholders who provide challenge and critical feedback.
• Experience leading projects and initiatives involving other resources (team members).
• Minimum of 4 years' on-the-job experience with pertinent statistical software packages (SAS, Python, Stata, R).
• 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.

• 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 5 years' statistical analysis programming experience.
• 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.
• Financial modeling experience…