PhD in Quantitative Finance – AI Research Evaluator | Outlier at Outlier Strategy | Torre

PhD in Quantitative Finance – AI Research Evaluator | Outlier

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Freelance
Recurrent
Compensation USD150/hour
location_on
Remote (for United States residents)
Remote (for Canada residents)
Remote (for Puerto Rico residents)
Remote (for Mexico residents)
Shared by
Jose Aldave
5 days ago

Responsibilities


Outlier is looking for PhD-level Quantitative Finance experts to help train and evaluate advanced AI models on financial reasoning, quantitative problems and financial modeling.What You'll DoEvaluate AI-generated finance and quantitative contentAssess factual accuracy and relevanceCreate and answer questions on Quant Finance, Financial Modeling and Applied MathematicsEvaluate and rank AI-generated responsesIdentify subtle errors in quantitative reasoningHelp improve the performance of advanced AI modelsRequired BackgroundPhD completed or in final stages in:Quantitative FinanceFinancial EngineeringFinancial MathematicsClosely related quantitative fields with a strong finance focusKey ExpertiseQuant Finance • Applied Mathematics • Financial Modeling • StatisticsStrong knowledge of areas such as:Stochastic ModelingDerivatives PricingEconometricsRisk ModelingComputational Finance⭐ Nice to HaveAcademic or industry research experienceBuy-side or sell-side quantitative experienceAI model evaluation or data annotation experienceResearch publication/review experienceCompensationUp to $150/hourActual compensation depends on expertise, experience and assessment performance. Quantitative finance specialists are specifically identified as highly sought-after experts.🌎 Eligible LocationsUnited StatesCanadaPuerto RicoMexicoUnited KingdomAustraliaNew ZealandArgentina⚠️ Location eligibility applies. Applicants should confirm they are based in an accepted country before applying.Why Consider This Opportunity? A strong opportunity for quantitative finance researchers and practitioners to apply their expertise to Generative AI research, evaluation and model improvement while working remotely on a flexible contract.