As a part of a global internal audit team, lead the development of next-generation model audit practices to maintain a best-in-class global internal audit function, specifically focusing on the integrity of algorithms driving the business.
Responsible for supporting the internal audit plan through the execution of technical model validations and model risk audits from beginning to end. Key activities include independent replication, code review, conceptual soundness assessment, back-testing analysis, and validation of remediated model findings.
Lead the validation of critical Financial Crime Compliance models, including Transaction Monitoring, Sanctions Screening, Customer Risk Rating, and Fraud detection models. You will ensure these models operate effectively and align with global regulatory requirements.
Review and evaluate the adequacy of management's response to audit findings, including the validation of complex remediation activities involving data lineage and algorithm tuning.
Develop technical audit reports on the effectiveness of model performance and governance for an executive-level audience, translating complex quantitative concepts into clear, actionable business insights.
Assist in the preparation of internal audit materials regarding the Model Risk portfolio for the Audit Committee and Board of Directors.
Establish and maintain trusted relationships with Data Science, Engineering, Product, and Compliance teams to foster a culture of robust model governance.
Work closely with first and second lines of defense to maximize testing efficiencies and ensure comprehensive coverage of the model inventory, minimizing duplication of efforts while maintaining 3rd Line independence.
Serve as a value-add advisor to business partners by identifying opportunities to enhance model precision, reduce false positives, and improve operational performance without compromising objectivity.

Requirements

A BA/BS degree in Statistics, Mathematics, Economics, Data Science, Engineering, or related quantitative fields.
8+ years of experience, with at least 5 years of experience in Model Risk Management, Model Validation, or Quantitative Audit within the financial services or fintech industry.
Specific experience with Financial Crime models: Deep understanding of the logic, data inputs, and tuning methodologies for AML Transaction Monitoring (rules-based and machine learning), Sanctions Screening (fuzzy logic, NLP), and Fraud models.
Technical Proficiency: Ability to read and review code. Proficiency in statistical programming languages such as Python, R, SQL, or SAS is essential.
Excellent understanding of the model development lifecycle (MDLC) and internal control environments surrounding data governance and model implementation.
Proven project management skills with the ability to juggle multiple complex technical validations and deadlines.
Solid analytical and problem-solving skills, with high standards for quality, accuracy, and attention to detail.
Excellent written and verbal communication skills; ability to explain models to non-technical stakeholders.
Experience leading and managing technical or co-sourced teams.
Experience auditing machine learning/AI models and/or familiarity with AI governance frameworks.

Benefits

medical
dental
vision
401(k)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Model Risk ManagementModel ValidationQuantitative AuditStatistical ProgrammingPythonRSQLSASModel Development LifecycleData Governance

Soft Skills

Project ManagementAnalytical SkillsProblem-SolvingAttention to DetailWritten CommunicationVerbal CommunicationRelationship BuildingTeam LeadershipAdaptabilityStakeholder Engagement