We are seeking a quantitative research intern for the Point72 Trading Research group. Specifically, we are looking for a researcher/developer with experience in deep learning models. Particularly in deep learning models for textual understanding/natural language processing (NLP).
The internship responsibilities would include:
- Parsing text-based financial data, including external data (like company news) and internal data.
- Building datasets for applied NLP problems, useful for trading and research in public markets.
- Building model training and evaluation pipelines.
- Exposing the outputs of trained models to users, including in real-time.
We believe that there have been significant advances in deep learning methods of text understanding over the past several years. We are working on taking advantage of these advances, for the applied finance domain.
An ideal candidate would be someone with significant technical skills, understanding, and prior experience in the deep learning space, a knowledge of NLP, and a curiosity about finance and trading.
- Master’s or PhD candidates in machine learning, computer science, or other related disciplines
- Proficient in Python
- Experience with deep learning-based NLP – PyTorch, HuggingFace Transformers, etc.
- Contribution to an open-source codebase is a plus, preferably in machine learning
- Prior experience (fulltime or internship) in software development is a plus
- Interested in applying machine learning to finance
- Willing to take ownership of his/her work, working both independently and within a small team