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Finance Expert - Quantitative Trading

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Reyes Beer Division
Full Time position
Listed on 2026-02-23
Job specializations:
  • Finance & Banking
    Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

About the Role

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.

Quantitative Trader’s Role in Advancing xAI’s Mission

You will directly contribute to xAI's mission by helping train and refine our frontier AI models. You will teach the models how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems. This involves providing high‑quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions.

We are looking for individuals who are enthusiastic about these data‑generation activities, as they form a core part of advancing xAI’s goals in scientific discovery and real‑world reasoning.

Scope

Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation. The role may include recording audio responses, participating in video‑based tasks, or producing step‑by‑step quantitative reasoning traces — all of which are essential job functions required to fulfill xAI’s mission. All outputs are considered work‑for‑hire and owned by xAI.

Responsibilities
  • Use proprietary annotation and evaluation software to provide precise labels, rankings, critiques, and detailed solutions on assigned projects
  • Deliver consistently high‑quality, curated data that meets strict technical and scientific standards
  • Collaborate with engineers and researchers to support the creation and iteration of new training tasks and evaluation benchmarks
  • Provide feedback that helps improve the usability, efficiency, and precision of annotation and data‑collection tools
  • Select and solve complex problems from quantitative trading domains where you have deep expertise. Examples include:
    • Factor model construction and signal combination
    • Market microstructure and order book dynamics
    • Statistical arbitrage and pairs/cointegration strategies
    • ML‑driven alpha generation and feature engineering
    • Optimal execution algorithms and transaction cost modeling
    • Portfolio construction under constraints (risk, turnover, sector, etc.)
    • Risk modeling and stress‑testing frameworks
  • Deliver rigorous model critiques, alternative solutions, mathematical derivations, and quantitative reasoning when evaluating AI outputs
  • Interpret, analyze, and execute tasks efficiently based on detailed (and sometimes evolving) instructions
Key Qualifications
  • Master’s or PhD in a strongly quantitative field such as Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Computer Science (with finance focus), Physics, Operations Research, or Econometrics, or equivalent professional experience as a quantitative researcher or 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, Fact Set, 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
Preferred Qualifications
  • Professional experience in quantitative trading, systematic strategies, or quant research at a hedge fund, prop trading firm, asset manager, or investment bank
  • Track record of publication(s) in refereed journals/conferences in finance, econometrics, machine learning, or related fields
  • Prior teaching, mentoring, or tutorial experience (university level or industry training)
  • Working proficiency in Python (pandas, Num Py, Sci Py,…
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