Finance Expert - Equity Research

xAI xAI · AI Frontier · Palo Alto, CA · Remote · Financial

The role focuses on creating training data, performing model evaluations, and providing annotations for AI models in the domain of equity research. The expert will partner with technical teams to ensure AI models accurately capture investment analysis complexity.

What you'd actually do

  1. Use proprietary software to deliver precise inputs, labels, and annotations for equity research projects, producing high-quality training data for AI models.
  2. Create and curate realistic, high-fidelity scenarios involving sector and company analysis, financial modeling, valuation methodologies (DCF, comparable companies, precedent transactions), earnings forecasts, investment thesis development, and research report preparation.
  3. Develop detailed examples of coverage initiation, earnings analysis, estimate revisions, industry specific data analysis and investment recommendation frameworks.
  4. Partner with technical staff to support the development of new AI tasks and contribute to innovative tooling.
  5. Help design and refine efficient annotation tools tailored to equity research workflows.

Skills

Required

  • Minimum of 2 years of professional experience in sell-side or buy-side equity research, with demonstrated sector coverage responsibility.
  • Proficiency in financial modeling, valuation techniques, and financial statement analysis.
  • Strong command of written and spoken English (informal and professional).
  • Excellent communication, interpersonal, analytical, and organizational skills.
  • Superior reading comprehension and ability to exercise sound independent judgment with incomplete or ambiguous information.
  • Genuine interest in technological innovation and its application to investment research.

Nice to have

  • Relevant certifications (e.g., FINRA licenses such as Series 7/63/86/87, current or expired).
  • Familiarity with Bloomberg, FactSet, Capital IQ, or similar research platforms.
  • Experience writing and publishing research notes, earnings summaries, or coverage reports for institutional clients.
  • Experience mentoring or training junior associates in research methodologies, modeling best practices, or report writing.
  • Quantitative mindset with ability to integrate structured data insights into fundamental analysis.
  • Comfort recording audio or video sessions for data collection purposes.
  • Prior exposure to AI, machine learning, data visualization, or data annotation workflows.

What the JD emphasized

  • high-quality training data
  • model evaluations
  • AI models
  • institutional-grade investment analysis
  • equity research

Other signals

  • training data
  • model evaluations
  • AI models
  • annotation