Demo

Part-time Intern (15-20 hours per week)

Capula
York, NY Part Time|Intern
POSTED ON 9/24/2025
AVAILABLE BEFORE 11/24/2025

Location: New York, NY (onsite, hybrid, or remote)
Commitment: 15–20 hours per week

About the Role

We are seeking a highly motivated PhD candidate in Finance to join our research team as an Off-Cycle Intern. This part-time role (15–20 hours per week) is designed for advanced doctoral students who are passionate about empirical finance, with a particular focus on global equities. The position offers the opportunity to work alongside experienced professionals, contribute to ongoing research initiatives, and apply academic expertise to practical investment challenges.

Key Responsibilities

  • Conduct empirical research on global equity markets using large-scale datasets (e.g., CRSP, FactSet, accounting, holdings, analyst forecasts, and other academically recognized sources).
  • Explore and analyze both traditional and behavioral equity return patterns.
  • Apply advanced econometric and statistical techniques to investment-relevant questions.
  • Develop, test, and refine quantitative models in Python.
  • Communicate findings clearly through written reports and verbal presentations to both technical and non-technical audiences.
  • Collaborate with researchers and portfolio managers on projects with direct application to investment strategies.

Education and Qualifications

  • PhD candidate in Finance (3rd year or beyond; exceptional earlier-stage candidates considered with prior relevant work experience).

Experience

  • Significant experience conducting empirical research in global equities using broad universe datasets.
  • Strong knowledge of equity market behavior, including both traditional and behavioral return patterns.

Technical skills:

  • 4 years of Python experience, with proficiency in Pandas, NumPy, and scikit-learn.
  • Completed graduate-level coursework in econometrics and statistics.
  • Excellent written and verbal communication skills.
  • Experience with industry risk models (e.g., Barra, Axioma) a plus.
  • Based in the New York area; role can be onsite, hybrid, or remote.

 

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