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.

Capula

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