Preparing for an interview at M&T Bank requires a balanced approach that combines sharp technical skills with a deep understanding of banking operations and risk management. You should approach your preparation not just as a test of coding, but as a demonstration of business acumen.

Role-Related Knowledge – You must demonstrate a strong command of SQL and SAS, as these are the cornerstones of the bank's data infrastructure. Be prepared to explain how you manipulate large datasets, build predictive models, and validate data integrity within a financial services context.

Problem-Solving & Analytical Rigor – Interviewers will evaluate how you structure ambiguous problems, such as forecasting charge-off losses or identifying portfolio variances. Focus on explaining your methodology step-by-step, showing how you transition from raw data to actionable business recommendations.

Communication & Stakeholder Management – As a Data Analyst, you will frequently interface with non-technical business partners and senior executives. You must show that you can translate complex quantitative concepts into clear, business-focused insights that drive strategic alignment.

Risk & Compliance Mindset – Working in a highly regulated banking environment means every analysis must adhere to strict internal governance and external regulatory standards. Demonstrating an innate understanding of risk appetite, auditability, and compliance is crucial to showing you are a fit for M&T Bank.

The interview process at M&T Bank is thorough and highly structured, typically taking anywhere from 4 to 8 weeks to complete. The bank places a heavy emphasis on ensuring candidates possess both the technical capability to handle complex financial data and the behavioral competencies required to collaborate effectively across the organization.

The journey begins with a standard recruiter phone screen, which focuses on your educational background, technical experience, and salary expectations. From there, you will progress to a technical screening, followed by a series of deeper interviews with hiring managers and peer panels. Because M&T Bank values cross-functional collaboration, you can expect to meet with multiple stakeholders, sometimes interviewing with up to four or more individuals throughout the final stages to gauge your fit within the broader team dynamic.

The visual timeline above outlines the typical progression from the initial application to the final offer. Candidates should use this structured flow to pace their preparation, ensuring they focus heavily on technical fundamentals in the early stages before shifting their attention to behavioral scenarios and domain-specific case studies as they approach the panel interviews. Note that while the sequence remains consistent, the depth of the technical rounds may vary depending on whether you are aligning with a highly quantitative risk team or a business-aligned analytics unit.

Statistical Modeling & SAS

Because M&T Bank relies extensively on legacy and modern statistical frameworks for credit risk modeling, your ability to leverage SAS and statistical theory is a primary evaluation area. Interviewers want to see that you understand the mathematical mechanics behind the models you build, rather than just running pre-written scripts.

Be ready to go over:

• Regression Analysis – Understanding linear and logistic regression, parameter estimation, and model diagnostics.
• Decision Trees – Building and pruning classification trees to segment customer risk profiles.
• Model Validation – Techniques for assessing model predictive power, such as ROC curves, Gini coefficients, and lift charts.
• Advanced concepts (less common) – Time-series forecasting, survival analysis for credit portfolios, and machine learning applications in credit scoring.

Example questions or scenarios:

• "Walk me through how you would handle missing data and outliers when preparing a dataset in SAS for a predictive model."
• "How do you interpret a discordance ratio or an AUC-ROC score when evaluating a credit default prediction model?"

SQL & Data Manipulation

To perform any analysis, you must first extract and clean the data. M&T Bank's databases are massive and highly relational, requiring analysts who can write efficient, optimized SQL queries without degrading database performance.

Be ready to go over:

• Complex Joins & Set Operations – Combining data from multiple transactional and demographic tables accurately.
• Aggregation & Window Functions – Utilizing PARTITION BY, RANK(), and rolling averages to analyze historical customer behavior.
• Query Optimization – Understanding execution plans, indexing, and avoiding costly operations like nested loops or unnecessary subqueries.
• Advanced concepts (less common) – Writing stored procedures, managing temporary tables, and understanding database schema designs.

Example questions or scenarios:

• "Write a SQL query to identify customers who have experienced more than three overdraft events within a rolling 30-day period."
• "Explain the performance implications of using a WHERE clause versus a HAVING clause in a complex aggregation query."

Credit Risk & Portfolio Monitoring

This evaluation area tests your domain expertise. To be successful, you must understand how a bank makes money, how credit risk impacts the balance sheet, and how macroeconomic factors influence customer behavior.

Be ready to go over:

• Credit Metrics – Understanding key performance indicators such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Loss Forecasting – Methodologies for predicting future charge-offs to support capital adequacy planning (such as CCAR).
• Variance Analysis – Identifying why actual portfolio performance deviated from forecasted expectations.
• Advanced concepts (less common) – Stress testing methodologies, macroeconomic scenario analysis, and the impact of interest rate changes on credit portfolios.

Example questions or scenarios:

• "If the bank decided to ease its credit policy for overdraft approvals, how would you set up a monitoring framework to evaluate the risk-return trade-off?"
• "How would you analyze and explain a sudden spike in credit card delinquencies during a period of economic growth?"

Behavioral & Competency-Based Evaluation

A significant portion of candidates fail the interview process during the competency-based rounds. M&T Bank values professionals who are resilient, highly collaborative, and capable of maintaining a professional demeanor even when facing challenging or disengaged stakeholders.

Be ready to go over:

• The STAR Method – Structuring your behavioral answers by clearly defining the Situation, Task, Action, and Result.
• Stakeholder Communication – Demonstrating your ability to influence business decisions and build consensus across teams.
• Handling Ambiguity – Showcasing how you deliver high-quality results when data is incomplete or project requirements change.
• Advanced concepts (less common) – Navigating corporate bureaucracy and managing conflicting priorities between risk management and business unit targets.

Example questions or scenarios:

• "Describe a time when you had to deliver bad news regarding portfolio performance to a business leader. How did you structure your communication?"
• "Tell me about a project where you had to work with minimal guidance. How did you determine your analytical approach?"