M&T Bank is seeking to develop and analyze quantitative/econometric behavioral models for credit risk, interest rate risk, and liquidity risk management, as well as balance sheet and capital planning. The role supports experienced analysts and management in data analysis, model development, and ad-hoc analysis to improve predictive results and identify risks and opportunities.
Requirements
- Minimum of 1 years’ statistical analysis programming experience
- Experience with pertinent statistical software packages such as SAS, Stata R or Python, especially SAS
- Credit Risk Modeling experience
- Logistic regression in credit risk modeling experience
- Fluency and high proficiency in econometric/statistical techniques, especially time-series analysis and logistic regression
- Monte Carlo simulation experience
- 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
Responsibilities
- 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.
- 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.
- Incorporate observations and data into existing models to improve predictive results.
- Support development and maintenance of satisfactory model documentation, including process procedures and performance monitoring guidelines to serve as reference source.
- Engage with colleagues in Model Risk Management for model validation exercises.
Other
- This is a hybrid position requiring in-office work three (3) days every week and it will be based in an Office in either Buffalo, NY, or Iseline, NJ.
- Proven experience in analyzing data sets and explaining results of analysis through concise written and verbal communication as well as charts/graphs
- 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
- Advanced knowledge of pertinent spreadsheet, word processing and presentation software
- Promote an environment that supports belonging and reflects the M&T Bank brand.
