Finance Expert – Quantitative Trading
Job Description:
• As a Quantitative Trader, you will play a key role in improving xAI's advanced AI systems by delivering high-quality annotations, evaluations, and expert input using specialized labeling tools.
• You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains.
• Your expertise will help select and solve challenging problems in systematic and quantitative strategies — including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimization under realistic constraints.
• This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.
• Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.
Requirements:
• Master’s or PhD in a strongly quantitative field: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Computer Science (with finance focus), Physics, Operations Research, Econometrics, or closely related discipline or equivalent professional experience as a quantitative researcher / systematic trader
• Excellent written and verbal communication in professional English (both technical and explanatory styles)
• Deep familiarity with financial data sources and platforms (Bloomberg, Refinitiv, FactSet, Capital IQ, SEC EDGAR, CRSP/Compustat, TAQ, earnings transcripts & call databases, alternative data providers, etc.)
• Exceptional analytical reasoning, attention to detail, and ability to make sound judgments with incomplete information
• Genuine passion for quantitative methods, systematic trading, machine learning in finance, and frontier AI technology.
• Professional experience in quantitative trading, systematic strategies, or quant research at a hedge fund, prop trading firm, asset manager, or investment bank (preferred qualification)
• Track record of publication(s) in refereed journals/conferences in finance, econometrics, machine learning, or related fields (preferred qualification)
• Prior teaching, mentoring, or tutorial experience (university level or industry training) (preferred qualification)
• Working proficiency in Python (pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow, statsmodels, polars, etc.) and/or R for financial modeling and data analysis (preferred qualification)
• Familiarity with backtesting frameworks, vectorized computation, and handling large financial datasets (preferred qualification)
• CFA, FRM, CQF, CAIA or similar professional designations (preferred qualification)
• Experience with high-frequency data, execution algorithms, or market microstructure research (preferred qualification)
• Previous work involving large language models, reinforcement learning, or AI evaluation pipelines (a strong plus) (preferred qualification).
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.
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• As a Quantitative Trader, you will play a key role in improving xAI's advanced AI systems by delivering high-quality annotations, evaluations, and expert input using specialized labeling tools.
• You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains.
• Your expertise will help select and solve challenging problems in systematic and quantitative strategies — including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimization under realistic constraints.
• This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.
• Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.
Requirements:
• Master’s or PhD in a strongly quantitative field: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Computer Science (with finance focus), Physics, Operations Research, Econometrics, or closely related discipline or equivalent professional experience as a quantitative researcher / systematic trader
• Excellent written and verbal communication in professional English (both technical and explanatory styles)
• Deep familiarity with financial data sources and platforms (Bloomberg, Refinitiv, FactSet, Capital IQ, SEC EDGAR, CRSP/Compustat, TAQ, earnings transcripts & call databases, alternative data providers, etc.)
• Exceptional analytical reasoning, attention to detail, and ability to make sound judgments with incomplete information
• Genuine passion for quantitative methods, systematic trading, machine learning in finance, and frontier AI technology.
• Professional experience in quantitative trading, systematic strategies, or quant research at a hedge fund, prop trading firm, asset manager, or investment bank (preferred qualification)
• Track record of publication(s) in refereed journals/conferences in finance, econometrics, machine learning, or related fields (preferred qualification)
• Prior teaching, mentoring, or tutorial experience (university level or industry training) (preferred qualification)
• Working proficiency in Python (pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow, statsmodels, polars, etc.) and/or R for financial modeling and data analysis (preferred qualification)
• Familiarity with backtesting frameworks, vectorized computation, and handling large financial datasets (preferred qualification)
• CFA, FRM, CQF, CAIA or similar professional designations (preferred qualification)
• Experience with high-frequency data, execution algorithms, or market microstructure research (preferred qualification)
• Previous work involving large language models, reinforcement learning, or AI evaluation pipelines (a strong plus) (preferred qualification).
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.
Apply tot his job
Apply To this Job