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Quantitative Research Intern (NLP)
Point72, L.P. · New York, NY · Posted May 31, 2025
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Job description
ROLE/RESPONSIBILTIES:
We are seeking a quant research intern to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing.
The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading.
Responsibilities may include:
- Using NLP to construct features from varied datasets
- Formulating research hypotheses to derive alpha
- Building and testing the performance of trading signals based on NLP and financial features
- Launching identified signals into production
REQUIREMENTS:
- Bachelor’s, Master’s or PhD candidate in computer science or other quantitative discipline
- Proficient in Python and general software engineering principles (github, testing, dev workflow)
- Strong understanding of machine learning and statistics
- Prior research experience preferred
- Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred
- Data science stack familiarity preferred
- An interest in financial markets
- Great attitude
- A collaborative mindset
- Commitment to the highest ethical standards
ABOUT POINT72:
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.
Source: this job was published on Point72, L.P.’s careers page (hosted on Greenhouse). VisaBacked doesn’t accept applications; you apply directly with the employer. Listing data refreshed daily; expired roles are removed within 24 hours.
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