Credit Model Development Quantitative Analyst I – HELOC, Residential Mortgage

M&T Bank

Quantitative Analyst developing econometric models for credit risk management at M&T Bank. Supporting data analysis and model development efforts related to balance sheet and capital planning.

Posted 7/16/2026full-timeBuffalo • Connecticut, District of Columbia, Maryland, New Jersey, New York, Virginia • 🇺🇸 United StatesJunior💰 $62,200 - $103,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quantitative model development and analysis for credit risk, interest rate risk, and liquidity risk management, utilizing advanced statistical techniques and programming skills. Proficient in data analysis and communication of results to stakeholders across banking and financial services.

Highest-signal resume keywords

Quantitative Model DevelopmentStatistical Analysis ProgrammingEconometric TechniquesSQL Data ManagementPython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Econometric ModelingStatistical AnalysisLinear RegressionLogistic RegressionData AnalysisModel ValidationFinancial Instrument ValuationData ManagementStatistical Software ProficiencyRisk Management

Soft Skills

Concise CommunicationTeam CollaborationAutonomous WorkLeadershipDesire to Learn

Tools & Technologies

SASStataRPythonSQLStatistical Software

Industry Keywords

BankingFinancial ServicesCredit RiskInterest Rate RiskLiquidity RiskCapital PlanningData AnalysisModel DocumentationPortfolio PerformanceRisk Strategy

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health insurance
401(k) matching
Forty hours of paid volunteer time each year
Professional development opportunities