The opportunity
Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades.
What you'll do
Model Validation & Review Execution: Perform independent, rigorous quantitative and qualitative analyses of rule-based and machine learning financial crimes surveillance models, filtering systems, and detection logic targeting model design, algorithm soundness, data integrity, and change management
Technical Review & Remediation: Act as a technical bridge within a fast-paced fintech environment by leveraging a solid foundation in data engineering, data modeling, and infrastructure. Collaborate seamlessly with software engineers, data engineers, and data scientists to decipher complex logic, evaluate model implementations, test data pipelines, and support the remediation of model issues.
Optimization & Model Tuning: Execute effective tuning methodologies and statistical analyses to continuously calibrate and enhance surveillance models. Work on strategic initiatives focused on maximizing risk detection capabilities while systematically reducing false positive volumes to ensure an efficient and effective alert review process.
Logic & Data Integrity Assurance: Conduct comprehensive data validation and logic testing initiatives to establish a strong foundation of data quality. Ensure the completeness, accuracy, and end-to-end reliability of critical data pipelines and inputs feeding our compliance models, mitigating systemic risks and safeguarding the integrity of our transaction monitoring ecosystem.
Subject Matter Expertise: Serve as a knowledgeable subject matter resource in AML and Model Risk, providing practical domain insights and supporting cross-functional partners in understanding model logic, performance, and risk trade-offs.
Cross-Functional Collaboration: Build strong working partnerships across engineering, product, and compliance teams to ensure technical solutions are conceptually sound, effective, and aligned with our risk tolerance.
What they're looking for
- Change & Issue Management: Uphold change and issue management policies for covered systems, models, and solutions, ensuring end-to-end traceability and maintaining defensible documentation for internal audit and external regulators.
- AI Strategy & Tech-Forward Adoption: Bring hands-on capabilities and experience leveraging AI tools, Large Language Models (LLMs), and automation techniques to enhance daily productivity, elevate deliverable quality, and optimize team workflows.
- Documentation & Reporting: Author thorough, concise, and defensible validation reports, change and issues management documentation, and executive summaries that clearly explain model theory, testing logic, performance findings, and actionable recommendations for key stakeholders.
