KeyBank is a financial institution that provides various banking services. They are seeking a Quantitative Analytics Associate who will be responsible for the independent validation and review of the bank's risk models to ensure compliance with regulatory requirements and proper functioning.

Responsibilities

• Perform hands-on quantitative model validation/review under supervision. This includes testing the model's conceptual soundness, data accuracy, methodology, and ongoing performance through techniques, such as back-testing, benchmarking, sensitivity analysis, stress testing, etc
• Provide an effective challenge throughout the model validation/review to ensure that models are robust, and all assumptions and limitations are justified
• Present findings, weakness and/or observations identified from the validation/review to model developers/owners to ensure executable finding remediations
• Prepare detailed validation reports and memos that document the validation approach, findings, and conclusions

Skills

• Bachelor's degree in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines
• One year of relevant analytics or modeling experience, or a graduate degree in a related field
• Experience in data handling, performing data transformations and data cleaning
• Experience in statistical testing and root-cause analysis
• Experience in traditional and AI/ML model development or validation, with a good understanding of quantitative modeling methods (including AI/ML algorithms) used for various risk predictive models, such as fraud risk, AML risk models, etc
• Proficiency in programming languages such as Python, R, SQL or SAS
• Excellent written and verbal communication skills to clearly articulate complex technical findings to both technical and non-technical stakeholders

Benefits

• Eligibility for incentive compensation which may include production, commission, and/or discretionary incentives
• Flexible options in circumstances where roles can be performed effectively in a mobile environment

Company Overview