Descripción de la oferta
Statistical Modeling AI/ML Model Evaluation Model Risk Management Python/R Scripting Technical Report Writing Best Backgrounds Banking Financial Services Insurance Consulting (Big 4) Fintech The AI Model Validator is a specialized, technically demanding “second line of defense” role. It exists primarily in financial services due to Federal Reserve SR 11-7/OCC guidance (issued 2011, superseded by SR 26-2 on April 17, 2026) mandating independent model validation. SR 26-2 explicitly excludes generative and agentic AI from scope, meaning organizations must build a dedicated AI governance layer alongside traditional validation. Deutsche Bank has a dedicated AI/ML Validation unit within Model Risk Management. Top employers: Citi, JPMorgan Chase, Deutsche Bank, Morgan Stanley, SMBC, Ally Financial, Santander, KeyBank, UBS, Barclays. Big 4 and risk consultancies (FRG Risk, RiskSpan) provide outsourced validation. Insurance, fintech (BioCatch), and tech (AMD) represent growing markets beyond the traditional banking concentration. Deutsche Bank has established a dedicated AI/ML Validation unit within its Model Risk Management division, with teams in Mumbai, Frankfurt, Berlin, London, and New York — representing the leading edge of the AI model validation specialization. SR 11-7 Three Pillars: SR 11-7 established the three pillars of model validation: (1) conceptual soundness — evaluating theoretical framework, methodology, and assumptions; (2) outcome analysis — comparing model outputs against actual outcomes; (3) ongoing monitoring — tracking model performance over time. Note: SR 26-2 superseded SR 11-7 on April 17, 2026, but explicitly excludes generative/agentic AI, creating a dual governance requirement. (Source: Federal Reserve SR 11-7, SR 26-2) AI Model Validator: Day in the Life Model Performance Review Review latest performance reports of deployed AI models, check for anomalies or degradation. Model Performance Review Review latest performance reports of deployed AI models, check for anomalies or degradation. REALITY CHECK + Conceptual Soundness Review Evaluate theoretical framework, methodology, and assumptions of models under validation. Conceptual Soundness Review Evaluate theoretical framework, methodology, and assumptions of models under validation. REALITY CHECK + Validation Planning Review validation schedule, prioritize engagements, assess resource requirements. Validation Planning Review validation schedule, prioritize engagements, assess resource requirements. REALITY CHECK + Sector Demand Insurance & Fintech MODERATE Job Posting Signals $157,740 average Quantitative Model Validation Analyst salary (Glassdoor, 35 salaries) SR 26-2 superseded SR 11-7 on April 17, 2026, explicitly excluding Gen AI from scope 96,000+ professionals globally hold the GARP FRM certification Competitive Landscape Glassdoor MVA average (91 salaries): $114,035 Glassdoor Quant MVA average (35 salaries): $157,740 MS/PhD requirement: Effectively non-negotiable Regulatory Drivers SR 26-2 (April 2026) — Superseded SR 11-7; explicitly excludes Gen AI/agentic AI, creating dual governance requirement SR 11-7/OCC — Original Federal Reserve model risk guidance; three-pillar validation framework remains influential EU AI Act — High-risk AI system conformity assessments require model validation expertise NIST AI RMF — Seven trustworthiness characteristics provide AI-specific validation criteria Skills & Certifications Skills Radar Self-Assessment Statistical Modeling 3 AI/ML Evaluation 2 Python/R Programming 2 Regulatory Knowledge 1 Report Writing 2 Bias & Fairness Testing 1 Gap Analysis Statistical Modeling AI/ML Evaluation Python/R Programming Regulatory Knowledge Report Writing Bias & Fairness Testing Certifications Command Table Exam Format Link 1 GARP FRM GARP $1,600–$2,000 total (2 parts) Part I: 100 MCQ 4hr, Part II: 80 MCQ 4hr; 2yr experience garp.org 2 GARP RAI GARP $525+ 80 MCQ; no prerequisites; bridges risk and AI governance garp.org 3 AIGP IAPP $649–$799 100 MCQ, 2hr 45m; no prerequisites; AI governance breadth TJS Guide | iapp.org GARP FRM Program — Gold standard for model risk professionals; two-part exam covering quantitative analysis, risk management, and financial markets $1,600–$2,000 ~240h study Advanced ISACA CRISC — Risk and information systems control; positions validators for enterprise risk committee engagement $575–$760 ~150h study Advanced Key Books & References 4 items Frameworks & Standards 4 items Tools & Platforms 4 items Feeder Roles Data Scientist $110K–$160K 2–3 yr Quantitative Analyst $100K–$150K 1–2 yr Actuary $90K–$140K 2–3 yr $80K–$120K 2–3 yr $70K–$110K 2–3 yr Current Role $150K–$200K Mid-Level Advancement Senior Validator / VP $142K–$200K 3–5 yr Director / SVP $187K–$240K+ 5–8 yr Head of Model Validation / MD $250K–$350K+ 8–12 yr $300K–$500K+ 12+ yr Entry MVA $77K–$128K Mid-Level / AVP $96K–$145K Senior / VP $142K–$200K Director / SVP $187K–$240K+ MD / CMRO $250K–$500K+ Contract Rate Independent MRM Consultant: $150–$300/hr Outsourced model validation engagements via risk consultancies (FRG Risk, RiskSpan, Big 4 advisory) 1 Walk me through the SR 11-7 three-pillar validation framework. 2 How would you build a challenger model for a credit scoring AI system? 3 Describe your approach to bias testing in an AI model used for hiring decisions. 4 How would you prepare for a regulatory examination of your model validation function? 5 How do you detect and handle model drift in production AI systems? Action Center Qualification Checker Click each card to flip it, then rate yourself. Complete all 10 to see your readiness score. 0 / 10 assessed MS/PhD Quantitative FRM GARP RAI Statistical Modeling Python/R AI/ML Evaluation Technical Reporting 90-Day Sprint Plan Builder Step 1: What’s Your Background? Data Scientist Quantitative Analyst Actuary Other Quantitative Background Knowledge Check Question 1 of 5 What are the three pillars of model validation established by SR 11-7? Conceptual soundness, outcome analysis, ongoing monitoring Community Hub Learn GARP FRM Program — gold standard for model risk professionals; quantitative risk certification “Fairness and Machine Learning” by Barocas, Hardt, Narayanan — free textbook on bias and fairness NIST AI RMF — seven trustworthiness characteristics for AI validation criteria NeurIPS / ICML Fairness Workshops — research-level engagement on AI fairness and evaluation Network GARP FRM Community — 96,000+ certified professionals globally; model risk specialization Model Risk Managers’ International Association (MRMIA) — dedicated model risk community Download free career transition templates, certification study guides, and skills checklists for AI security roles. #J-18808-Ljbffr
