Overview

This position supports the development of statistical and machine learning models within a regulated environment. The role contributes to key components of the model development lifecycle—including data preparation, model development, testing/validation support, implementation, and monitoring—while working closely with senior modelers to deliver analytically sound and well-documented solutions. Development work is performed using both Python and SAS.

Primary Responsibilities

• Support the design, development, testing, implementation, and monitoring of statistical and machine learning models
• Prepare, transform, and analyze large datasets (e.g., transactions, customer behavior, entity data)
• Partner with senior team members to translate business problems into analytical approaches
• Contribute to model documentation, including methodology, assumptions, and monitoring frameworks
• Develop and maintain analytical code using Python and/or SAS
• Assist in model performance monitoring and identification of model issues or limitations
• Support model validation, audit, and regulatory review processes
• Collaborate with stakeholders across EDD, FIU, Technology, and Model Risk Management
• Ensure adherence to internal controls and regulatory expectations
• Provide guidance to junior analysts where appropriate
• 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.

Scope of Responsibilities

Works under general guidance from more senior quantitative risk managers. Responsible for independent execution of defined analytical tasks and contributing to model development efforts. Builds technical expertise in AML modeling and governance.

Education and Experience Required

• Bachelor degree in Mathematics, Statistics, Quantitative Analysis or another technical discipline,
• OR in lieu of degree A combined minimum of  7 years higher education and/or work experience to include a minimum of 3 years relevant experience.
  -OR-
• Master’s degree in Mathematics, Statistics, Quantitative Analysis or another technical discipline, with minimum of 1 year relevant experience,
  OR in lieu of degree,
• A combined minimum of  7 years higher education and/or work experience to include a minimum of 1 year relevant experience.
• Minimum of 3 years relevant experience, Banking or Financial Services experience.

Preferred

• Master’s degree in a quantitative discipline
• Experience in banking, financial services, or AML/BSA
• Exposure to model validation or model risk management
• Familiarity with machine learning techniques

Location