Note: The job is a remote job and is open to candidates in USA. Cash App, a dynamic financial ecosystem company, is seeking a Senior Data Scientist specializing in AI and Model Risk to lead AI risk assessments for generative AI and Large Language Models. The role involves applying Model Risk Management principles to ensure safe and compliant AI deployment, collaborating with multiple stakeholders across Risk, Engineering, Legal, Compliance, and Information Security. This position is central to shaping AI risk governance practices within financial services.
Responsibilities
- Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank; Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
- Review AI system design and documentation; Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
- Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
- Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
- Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
- Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program; support SFS's response to regulatory inquiries as needed
Skills
- A minimum of 5 years of related experience with a Bachelor's degree in a quantitative field; or 3 years and a Master's degree; or a PhD without experience; or equivalent work experience in risk management, model risk management, or AI risk management
- Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
- Strong understanding of generative AI architectures; Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
- Understanding of interagency model risk management principles, including SR 26-2
- Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
- Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators
- Strong analytical judgment with the ability to manage multiple concurrent assessments, prioritize effectively, and drive risk-based decisions with minimal day-to-day oversight
- Master's degree in AI/ML, Cybersecurity, Data Science, or related field
- Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001, or equivalent) and the FFIEC IT Examination Handbooks
- Experience with AI governance tools and platforms (model registries, monitoring dashboards, risk scoring systems)
- Experience with explainability tools (SHAP, LIME, attention visualization)
- Certifications: CRISC, PRM, FRM, or AI-specific certifications such as NIST AI RMF practitioner or ISO 42001 Lead Implementer
- Prior experience in a second-line-of-defense or internal audit role at a bank or financial institution
- Experience developing AI risk governance frameworks in environments where prescriptive regulatory guidance does not yet exist
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning
Company Overview
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