Job Description
Title: Model Risk Analyst – Validation
Job Location: One M&T Plaza, Buffalo, NY 14203.
Job Description: 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.
Minimum 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.
Requires Three (3) years of experience in each of the following:
- Programming Languages, including Python, MATLAB, C/C++, R and SAS.
- 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.
- Technical Writing, including writing technical reports using Microsoft Word, LaTeX, Markdown, or Git.
- 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.
- 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.
- Conducting independent review and validation of Machine Learning Models.
Skills can be gained through graduate-level coursework.
Salary: $91,463.04-$101,463.04 per year