Finance Expert - Risk

xAI xAI · AI Frontier · Remote · Financial

This role focuses on providing high-quality annotations, expert evaluations, and detailed risk reasoning using specialized labeling tools to support the development and refinement of AI capabilities in quantitative financial risk management. The expert will train and refine AI models by generating data across text, voice, and video formats, including annotations, critiques, calculations, and explanations, with a focus on market risk, credit risk, liquidity risk, operational risk, and regulatory compliance.

What you'd actually do

  1. Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects
  2. Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards
  3. Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks
  4. Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools
  5. Select and solve challenging problems from financial risk domains where you have deep expertise — examples include:

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • quantitative rigor
  • regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.)
  • quantitative risk management
  • model risk management
  • regulatory documentation

Other signals

  • train and refine frontier AI models
  • quantitative financial risk management domains
  • rigorous resolution of complex risk-related problems
  • generate high-quality data across text, voice, and video formats