Quantitative Risk Analyst - Indirect Lending

***Position can sit remote, hybrid, or fully in the office.

Perform advanced data and statistical analysis in support of the creation and maintenance of statistical models, including Regression and Multivariate models. Support Senior Analysts and Managers in data analysis and model construction.

• Assist in establishing, monitoring, evaluating and interpreting data with a risk management focus with an understanding of business strategy.
• Develop and maintain working knowledge of Credit Risk databases to provide data and analytical support to Senior Management.
• Perform data manipulation and analysis using SQL, SAS and Microsoft Excel and present results and recommendations to Credit Risk Management.
• Track portfolio performance and risk strategy results. Incorporate observations and data in to existing models to improve predictive results.
• Identify deviations from forecast/expectations and explain variances. Identify risk and/or opportunities.
• Track portfolio performance and risk strategy results. Incorporate observations and data in to existing models to improve predictive results.
• 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 diversity 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.

Bachelor degree in Mathematics, Statistics, Quantitative Analysis or another technical discipline,

OR in lieu of degree,

A combined minimum of 6 years higher education and/or work experience to include a minimum of 2 years relevant experience. -OR- Master’s degree in Mathematics, Statistics, Quantitative Analysis or another technical discipline.

Minimum of 2 years relevant experience

Banking or Financial Services experience.

Credit Analysis experience preferred. Experience with SAS, SAS Enterprise Miner and other Statistical Software Packages.

Advanced Knowledge of SQL and Microsoft Office.

Ability to utilize analytics in a collaborative manner across business functions and product lines to derive optimum solutions.

Demonstrated ability to communicate complex concepts.