Description
About the Role
As a Finance Risk Expert, you will be essential in advancing xAI's cutting-edge AI systems by providing high-quality annotations, expert evaluations, and detailed risk reasoning using specialized labeling tools. You will collaborate closely with technical teams to support the development and refinement of new AI capabilities, with a primary focus on quantitative financial risk management domains.
Your expertise will drive the selection and rigorous resolution of complex risk-related problems — including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing & scenario analysis, Value at Risk (VaR)/Expected Shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.). This role requires exceptional quantitative rigor, rapid adaptation to evolving guidelines, and the ability to deliver precise, technically sound critiques, derivations, and solutions in a fast-paced environment.
Finance Risk Expert’s Role in Advancing xAI’s Mission
As a Finance Risk Expert, you will directly support xAI's mission by helping train and refine frontier AI models. You will teach the models how risk professionals quantify uncertainties, model tail events, assess portfolio vulnerabilities, ensure regulatory compliance, perform stress testing, and make data-driven decisions to protect capital and maintain financial stability.
This involves generating high-quality data across text, voice, and video formats: detailed annotations, model critiques, step-by-step risk calculations, audio explanations of methodologies, and occasional structured video sessions. We seek individuals enthusiastic about these core data-generation activities to advance xAI’s goals in scientific discovery, complex system reasoning, and real-world risk assessment.
Scope
Finance Risk Experts provide labeling, annotation, evaluation, and expert reasoning services in text, voice, and video modalities to support model training and evaluation. Tasks may include recording audio walkthroughs of risk models, participating in video-based scenario reasoning, or producing detailed quantitative risk analysis traces — all essential functions to fulfill xAI’s mission. All outputs are considered work-for-hire and owned by xAI.
Responsibilities
- Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects
- Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards
- Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks
- Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools
- Select and solve challenging problems from financial risk domains where you have deep expertise — examples include:
- Market risk modeling (VaR, ES, historical/s Monte Carlo simulation, parametric methods)
- Credit risk and counterparty credit risk (PD/LGD/EAD modeling, CVA/DVA/FVA, wrong-way risk)
- Liquidity risk and funding risk (LCR/NSFR, stress liquidity gaps, contingent funding)
- Operational and model risk assessment & governance
- Stress testing, scenario analysis, and reverse stress testing (CCAR/DFAST, ICAAP)
- Risk attribution, decomposition, and backtesting frameworks
- Economic capital, regulatory capital (Basel III/IV), and risk-adjusted performance metrics (RAROC)
- Climate/ESG risk integration and emerging non-financial risks
- Deliver rigorous critiques of model outputs, alternative approaches, mathematical derivations, sensitivity analyses, and quantitative reasoning traces when evaluating AI responses
- Interpret, analyze, and execute tasks efficiently based on detailed (and sometimes evolving) instructions
Key Qualifications
- Master’s or PhD in a quantitative discipline:
- Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Econometrics, Risk Management, Operations Research, - - ---- Physics, Computer Science (with risk/finance focus), or closely related field or equivalent professional experience as a quantitative risk analyst, risk modeler, or risk quant
- Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)
- Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)
- Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data
- Genuine passion for quantitative risk management, financial stability, regulatory frameworks, extreme event modeling, and the application of frontier AI to risk problems
Preferred Qualifications
- Professional experience in quantitative risk management, model development/validation, or risk analytics at a bank, hedge fund, asset manager, insurance company, regulator, or consulting firm (e.g., market/credit risk quant, model risk management)
- Track record of publication(s) or contributions in refereed journals/conferences on risk, econometrics, statistics, or quantitative finance
- Prior teaching, mentoring, or training experience (university, industry workshops, regulatory training)
- Proficiency in Python/R for risk modeling (pandas, NumPy, SciPy, statsmodels, QuantLib, PyTorch/TensorFlow for ML risk models, etc.) and familiarity with risk systems (Murex, Calypso, Numerix, etc.)
- Experience with Monte Carlo simulation, copula models, stochastic processes, time-series analysis, extreme value theory, or machine learning for risk (anomaly detection, credit scoring, etc.)
- Knowledge of regulatory capital frameworks (Basel III/IV, FRB CCAR, SR 11-7 model risk guidance, IFRS 9/CECL, Solvency II)
- CFA, FRM, PRM, CQF, or similar risk-focused certifications
- Previous exposure to large language models, AI safety, or quantitative evaluation pipelines (strong plus)
Location & Other Expectations
- This position is based fully remote.
- If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time.
- We are unable to provide visa sponsorship.
- Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter.
- For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.
Compensation
$45/hour - $100/hour
The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location.
Benefits:
Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.
