Quantitative Researcher - Machine Learning
At a glance
Mid-level AI Research role at Point72. New York · full-time · no salary stated · we estimate $181,850–$300,000.
Point72 has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Run research from initial ideas through model choice, implementation, testing and eventual use
- Adapt or extend machine learning models, and create new approaches when needed, to produce trading signals or predict other variables
- Track AI and machine learning developments, then recommend models and tools and flag promising opportunities
What you bring
- A master’s or PhD in machine learning, computer science, statistics or another related field
- Hands-on machine learning research with large datasets, including data that may be noisy
- Strong skills with Torch, JAX or another listed machine learning library
- Python ability, cluster-environment competence and sound software engineering practices
Who this fits
This role suits a quantitative machine learning researcher who can work closely with other researchers and communicate their work. Financial-industry experience is not required.
From the employer
JOB RESPONSIBILITIES:
A highly collaborative, fast-growing team at Internal Alpha Capture (IAC), Point72 is developing AI-driven equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, proprietary data sources, and unparalleled computing power.
We are looking for exceptional machine learning researchers to join our efforts. Researchers will work closely with our experienced team members and apply the full breadth of their machine learning knowledge to unique, proprietary datasets, and develop novel trading signals that have high impact. Prior experience in the financial industry is not required.
Key responsibilities may include:
- Managing all aspects of the research process, including ideation, method selection, implementation, evaluation, and eventual application.
- Identifying, adapting, and extending existing models in the broad field of machine learning; conducting novel research as needed, to develop new signals that can enhance portfolio returns, or predict other variables of interests.
- Staying up to date on the advances in AI/ML and related technological innovations to provide recommendations on new models and tools and identify emerging opportunities.
DESIRABLE CANDIDATES:
- Master’s or PhD in machine learning, computer science, statistics, or related fields.
- Knowledge and experience in any of the following areas are strongly preferred: modern sequence models, graph neutral nets, reinforcement learning, LLMs.
- Prior research experience utilizing machine learning over large, possibly noisy, data sets.
- Strong analytical and quantitative skills, and a detail-oriented mindset.
- Strong proficiency in machine learning libraries such as Torch, JAX or TensorFlow.
- Competence in Python, cluster environment, and general software engineering principles (source control, testing, collaborative workflow).
- Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment.
- Commitment to the highest ethical standards.