Model Risk Analyst-Validation

M&T Bank•Buffalo, NY

1d•$91,463 - $101,463•Onsite

About The Position

Ensure the accuracy, reliability, and compliance of models in accordance with Company or regulatory standards and policies. Perform validation and analysis of expert judgment or qualitative factors that augment quantitative models. Analyze financial data, trends, and regulations to identify potential opportunities for improvement. Develop new models to address changing risk environments. Monitor model performance, prepare reports for internal and external stakeholders, and document findings. Stay abreast of industry best practices and regulatory changes. Provide guidance and advice to other departments regarding model risk management. Prepare written summary and analysis of all validation work, using a combination of word processing and presentation software skills.

Requirements

Master’s degree (or foreign equivalent) in Applied Mathematics, Computing, Data Science, Materials Science, or related STEM field of study plus three (3) years of experience as a Model Risk Analyst, Data Scientist, Quantitative Analyst, Product Developer, or related occupation.
Three (3) years of experience in Programming Languages, including Python, MATLAB, C/C++, R and SAS.
Three (3) years of experience in Technical Analyses, including in-sample back-testing, moving averages, time series analysis, z-score analysis, performance metrics evaluation, goodness-off-fit tests (including Kolmogorov-Smirnov test and Gini scores), and correlation matrices.
Three (3) years of experience in Technical Writing, including writing technical reports using Microsoft Word, LaTeX, Markdown, or Git.
Three (3) years of experience in Data Science concepts, including statistics and probability, exploratory data analysis (EDA), machine learning, model evaluation and selection, feature engineering, time series analysis, loss forecasting, and model validation concepts such as cross validation, model performance metrics selection, and bias-variance tradeoff.
Three (3) years of experience in Building Regression Models (including Linear and Logistic Regression and Multinomial Regression Models) and handling multicollinearity, assumptions review, and evaluation of regression models using various validation techniques.
Three (3) years of experience in Conducting independent review and validation of Machine Learning Models.
Skills can be gained through graduate-level coursework.

Responsibilities

Perform validation and analysis of expert judgment or qualitative factors that augment quantitative models.
Analyze financial data, trends, and regulations to identify potential opportunities for improvement.
Develop new models to address changing risk environments.
Monitor model performance, prepare reports for internal and external stakeholders, and document findings.
Stay abreast of industry best practices and regulatory changes.
Provide guidance and advice to other departments regarding model risk management.
Prepare written summary and analysis of all validation work, using a combination of word processing and presentation software skills.