Data Solutions & Validation Sr. Specialist

About the Team + Role

The Financial Crimes Team at Robinhood works across multiple verticals to protect our customers and ensure strict compliance with all relevant Anti-Money Laundering (AML) and Sanctions regulations. As our team of passionate professionals continues to evolve the program, we are intensely focused on leveraging innovative thinking, advanced analytics, and cutting-edge technology to build a best-in-class Financial Crimes Program.

As the Senior Specialist, Model Validation & Analytics, you will play a key role in this mission by executing the validation, testing, tuning, and optimization of various transaction monitoring and filtering programs across Financial Crimes. You will partner closely with the AML Surveillance Team, engineering partners, and cross-functional verticals to ensure our financial crimes models and systems are accurately implemented, rigorously evaluated, and effectively calibrated to meet regulatory requirements.

This role is based in our Denver, CO, New York, NY, or Westlake, TX office(s), with in-person attendance expected at least 3 days per week.

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 fintech environment by leveraging data engineering, data modeling, and infrastructure. Collaborate 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, maximizing risk detection while systematically reducing false positives.
• Logic & Data Integrity Assurance: Conduct comprehensive data validation and logic testing initiatives to establish data quality. Ensure completeness, accuracy, and reliability of critical data pipelines and compliance model inputs.
• Subject Matter Expertise: Serve as an AML and Model Risk resource, providing practical domain insights and explaining model logic, performance, and risk trade-offs to cross-functional partners.
• Cross-Functional Collaboration: Build strong working partnerships across engineering, product, and compliance teams to ensure technical solutions are conceptually sound and aligned with risk tolerance.
• Change & Issue Management: Uphold change and issue management policies, maintaining end-to-end traceability and defensible documentation for internal audit and external regulators.
• AI Strategy & Tech-Forward Adoption: Leverage AI tools, Large Language Models (LLMs), and automation techniques to elevate productivity, quality, and workflows.
• Documentation & Reporting: Author defensible validation reports, change/issue management documentation, and executive summaries explaining model theory, testing logic, performance findings, and actionable recommendations.

What You Bring

• Education: Bachelor's Degree or equivalent in a quantitative, technical, or financial field (e.g., Computer Science, Data Analytics, Statistics, or Finance).
• Experience: 5+ years of experience across AML, Financial Crimes, or risk management within financial services or fintech, focused on model validation, quantitative analysis, or surveillance system management.
• Domain Expertise: 3+ years of direct experience in the verification, validation, testing, or tuning of AML rule-based systems and/or machine learning models, with working knowledge of core Model Risk Management (MRM) principles and governance standards.
• Technical & Analytical Skills: Proficiency in SQL and experience using quantitative tools or programming languages (e.g., Python, R) to query large datasets, perform statistical analyses, and evaluate model performance.
• Adaptability & Communication: Excellent verbal and written communication skills to explain complex quantitative concepts to non-technical partners, with ability to manage competing priorities in a fast-paced environment.