Quantitative Risk Manager Jobs in Buffalo, NY (NOW HIRING)

Assists in development and analysis of quantitative/econometric behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning. Supports more experienced analysts and management in data analysis, model development efforts and ad-hoc analysis as needed.

• Assist in researching and developing quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning, including but not limited to, loan delinquency, default and loss models, loan prepayment and utilization models, deposit attrition models and financial instrument valuation methods.
• Prepare, manage and analyze large customer loans and deposit data sets for statistical analysis in Structured Query Language (SQL) or similar tool to properly specify and estimate econometric models to understand customer or Bank behavior for purposes of interest rate, liquidity or stressed capital risk.
• Understand the context of the Bank's data and businesses to ensure properly developed models.
• Produce and run regressions (including time series and logistic regression), programming routines and other econometric analyses to specify models using appropriate statistical software; communicate results, including graphic and tabular forms of model development activities to fellow team members, Treasury management and Bank-wide stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
• Execute models in production environment; communicate analytical results to Bank-wide stakeholders. Track portfolio performance, model performance, campaign tracking and risk strategy results.
• Incorporate observations and data into existing models to improve predictive results. Identify deviations from forecast/expectations and explain variances. Identify risk and/or opportunities.
• Support development and maintenance of satisfactory model documentation, including process procedures and performance monitoring guidelines to serve as reference source.
• Provide financial analysis and data support to other groups/departments across the Bank as required.
• Engage with colleagues in Model Risk Management for model validation exercises.
• 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 risk/model controls and other second line of defense policies and regulatory standards, policies and procedures.
• 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.
• Promote an environment that supports belonging and reflects the M&T Bank brand.
• 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.

The position uses statistical programming languages to analyze Bank datasets and develop, implement and maintain 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 recipients to understand the analyses. The position partners and collaborates with colleagues in related functions, including Asset Liability and Liquidity Management, Model Risk Management and business lines to implement and understand models for Bank use. 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 is a key factor of success in this role.

Not Applicable

• Bachelor's degree from accredited four year institution, or in lieu of a degree, a combined minimum of 4 years' higher education and/or work experience
• Proven experience in analyzing data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
• Model development experience

• Bachelor's degree in Statistics, Economics, Mathematics, Finance or related field in the quantitative social, physical, natural or engineering sciences, inclusive of proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
• Prior experience in banking and financial services industry
• One or more years of statistical analysis programming experience
• Experience with pertinent statistical software packages such as SAS, Stata R or Python- Python experience is highly preferred
• Fluency and high proficiency in econometric/statistical techniques, especially linear regression and logistic regression
• Proven track record for being able to work autonomously, within a team environment, exhibiting demonstrated leadership and a strong desire to learn and contribute to a group
• Minimum of 1 years' proven quantitative or data-oriented experience, including on-the-job use of statistical data analysis and data management environment such as SQL
• Advanced knowledge of pertinent spreadsheet, word processing and presentation software