Model Risk Analyst – Validation [Multiple Positions Available]

M&T Bank•Buffalo, NY

23h•Hybrid

About The Position

Perform independent validation review of complex financial statistical models with primary focus on Treasury models (including interest rates sensitive, interest rates and currency derivatives models), as well as Fair Lending and general Credit Risk models. Writing quality reports for management review. Preparing materials and leading Effective Challenge presentations of accomplished validations. Supporting MRM model life cycle in relations to reviewing and reporting of IRA, MCA, MCM, MRT. Establishing communication with model owners, model developers, model stakeholders in support of successful model validation process and MRM initiatives. Supporting development of playbook for Validation of Fair Lending Models. Coordinate the engagement of third parties to perform validation. Review the results of third party validation. Perform validation and analysis of expert judgment or qualitative factors that augment quantitative models. Review to confirm proper controls and adequate documentation are in place. Recommend, as necessary, the cessation of reliance on models that are outdated or inaccurate, as determined by analysis. Prepare reporting for Management to monitor performance of models. Participate in meetings with model owners to discuss current portfolio tracking and business observations. Develop knowledge on standard concepts, practices, and procedures within the model validation/risk analytics field. Mine data from a variety of sources. Utilize technical skills to manage data and efficiently conduct analyses. Develop ad hoc processes to address efficiency gains that translate into repeatable procedures. Prepare written summary and analysis of all validation work, using a combination of word processing and presentation software skills. Adhere to applicable compliance/operational risk controls in accordance with Company or regulatory standards and policies. 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.

Requirements

Master’s degree (or foreign equivalent) in Financial Mathematics, Mathematics, Statistics, Computer Science, Operation Research, Econometrics, or a related technical field plus three (3) years of experience in the job offered or as a Model Risk Analyst, Quantitative Model Developer, Quantitative Financial Analyst, Statistician, Data Scientist, or Model Validator.
Alternatively, a Bachelor’s degree (or foreign equivalent) in Financial Mathematics, Mathematics, Statistics, Computer Science, Operation Research, Econometrics, or related technical field plus six (6) years of experience in the job offered or as Quantitative Model Developer, Quantitative Financial Analyst, Statistician, Data Scientist, or Model Validator.
Three (3) years of experience in statistical modeling techniques including regression (including linear, logistic, Poisson, lasso, and ridge), machine learning (including tree and XGBoost), and cluster analysis.
Three (3) years of experience in programming skills in Python or SAS.
Three (3) years of experience in work with supervised models (including regressions, boosting, and ensemble learning) and unsupervised algorithms (including clustering and DBSCAN) applied to quantitative risk modeling and data-driven analysis.
Three (3) years of experience in statistical theory, including sampling methods, confidence intervals, and hypothesis testing for evaluating model assumptions and performance.
Three (3) years of experience in programming languages including Python or SAS for statistical modeling, machine learning development, implementation, future engineering and model performance evaluation.
Three (3) years of experience in writing reproducible code.
Three (3) years of experience in data wrangling, automation, and generating analytical reports.
Three (3) years of experience in leveraging SQL and other query languages to query, transform, and preprocess structured and unstructured data for analytical and modeling purposes.
Three (3) years of experience in working with data mining and feature engineering techniques.

Responsibilities

Perform independent validation review of complex financial statistical models with primary focus on Treasury models (including interest rates sensitive, interest rates and currency derivatives models), as well as Fair Lending and general Credit Risk models.
Write quality reports for management review.
Prepare materials and lead Effective Challenge presentations of accomplished validations.
Support MRM model life cycle in relations to reviewing and reporting of IRA, MCA, MCM, MRT.
Establish communication with model owners, model developers, model stakeholders in support of successful model validation process and MRM initiatives.
Support development of playbook for Validation of Fair Lending Models.
Coordinate the engagement of third parties to perform validation.
Review the results of third party validation.
Perform validation and analysis of expert judgment or qualitative factors that augment quantitative models.
Review to confirm proper controls and adequate documentation are in place.
Recommend, as necessary, the cessation of reliance on models that are outdated or inaccurate, as determined by analysis.
Prepare reporting for Management to monitor performance of models.
Participate in meetings with model owners to discuss current portfolio tracking and business observations.
Develop knowledge on standard concepts, practices, and procedures within the model validation/risk analytics field.
Mine data from a variety of sources.
Utilize technical skills to manage data and efficiently conduct analyses.
Develop ad hoc processes to address efficiency gains that translate into repeatable procedures.
Prepare written summary and analysis of all validation work, using a combination of word processing and presentation software skills.
Adhere to applicable compliance/operational risk controls in accordance with Company or regulatory standards and policies.
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.