Quantitative Researcher - Machine Learning
Point72 is hiring a Quantitative Researcher - Machine Learning in New York and Hong Kong. Level rates it ; you can apply on Point72.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions TensorFlow and JAX among its tools and skills.
- Point72 has 199 other open roles on Level.
AI in this role
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.
How we rate this
Quantitative Researcher - Machine Learning at Point72 rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used JAX in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: TensorFlow and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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