Quant Analytics Sr. Associate- Model Risk

Location:127 Public Square, Cleveland OhioABOUT THE JOBAs a Senior Quantitative Analytics Associate, you will be responsible for leading independent validations and reviews of the bank's various risk models. This role ensures that models are functioning as intended, comply with regulatory requirements, and that their risks are accurately identified, measured, and reported to senior management. Specifically, you will be performing in-depth validations and reviews of new and existing models used across the bank, including those for fraud risk, compliance risk (such as AML, OFAC), and/or other areas.ESSENTIAL JOB FUNCTIONSPerform hands-on quantitative model validation/review. This includes testing the model's conceptual soundness, data accuracy, methodology, and ongoing performance through techniques like backtesting, benchmarking, and 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 and provide them with executable finding remediations.Prepare detailed validation reports and memos that document the validation approach, findings, and conclusions.Participate in internal audits and regulatory exams by presenting validation results and methodologies and assisting in the remediation of any audit or exam findings.Act as a subject matter expert on modeling techniques, risk management practices, and regulatory trends. This involves performing research and developing advanced analytical tools or benchmarking models to aid the validation process.REQUIRED QUALIFICATIONSMaster's degree (or its equivalent) in a quantitative discipline and at least 3 years of relevant experience; or Bachelor's degree (or its equivalent) and at least 5 years of relevant experience.Hands-on experience in statistical and AI/ML model development or validation, with a strong 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 stakeholder.Knowledge of model risk management policies, procedures, and relevant regulatory guidance (e.g., from the OCC).EXPECTED COMPETENCIESLeadership: Emerging leader across team; Role model to others - may coach and develop; Provides direction/mentorship to junior staffPartnering / Influencing: Proven relationship building ability; Strong interpersonal skills; Can lead the conversation with partners in the business, technology, etc.; Sought out to by business partners and team members; May coach and develop relationship building skills in others; Developing comfort with influencing and consulting typically with mid-level leadersBusiness Acumen: Understands assigned LOB strategy; Knows our competition and industry; Possesses intellectual curiosity; Understands key drivers of financial results and business impact; Aware of the competitive environmentCritical Thinking / Problem Solving: Leverages critical thinking and business acumen to provide solutions to increasingly more complex problems; Understands impacts / intersections with other business partners / LOBs; Aware of potential pitfalls with each recommended solution; thoroughly vets and thinks through options before making a decisionCommunication: Strong writing skills; organizes material for brevity, persuasiveness, and impact; Effectively communicates key points to respective stakeholders, with the right amount of detail; Proactively shares information beyond those at the table who may have a need to know; Comfortable in situatio

Created: 2025-12-09