Machine Learning Researcher
- Location
- New York City, NY
- Compensation
- Competitive base + bonus
- Firm Type
- Hedge Fund
What You'll Be Doing
As a Machine Learning Researcher, you will develop ML/DL models to generate alpha from large-scale financial and alternative datasets. You will work closely with portfolio managers and senior quantitative researchers to conduct research across a range of trading strategies within a fast, iterative research-feedback loop.
Who We're Looking For
- Master’s or PhD from a top-tier university in a quantitative discipline (e.g., mathematics, physics, statistics, computer science, or related fields)
- Strong foundation in machine learning, statistics, and optimization, with deep expertise in at least one area such as time series modeling, NLP, or LLMs
- Strong communication skills and ability to collaborate effectively in a research-driven environment
- Experience with the Python scientific and ML ecosystem (e.g., NumPy, Pandas/Polars, PyTorch, TensorFlow)
- Proven ability to build and improve models that perform under noisy, non-stationary, and high-dimensional data conditions
- Intellectually curious, highly analytical, and driven to discover alpha in complex systems
- Self-motivated and highly productive, with strong ownership and a bias toward action
- Publications at top-tier venues such as NeurIPS, ICML, KDD, or IJCAI
- Strong track record in competitive ML platforms (e.g., Kaggle) or academic competitions
- Prior experience in quantitative research, systematic trading, or alpha signal generation
Why This Role
This is an exceptional opportunity to join a dynamic team at the forefront of quantitative finance. You will have the chance to leverage your expertise in machine learning to uncover profitable trading strategies, while collaborating with some of the brightest minds in the industry. Your contributions will directly impact the firm's success and your career trajectory.
Interested in this role?
Apply in a couple of minutes — résumé and a few details.