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Point72
Verified live 2d ago

Quantitative Researcher - Machine Learning

Brief overview

New York, New York, United StatesIn-person
MastersOr in progress
135 H-1B approvalsDept. of Labor
43 green cardsCertified filings
Machine LearningAI ResearchPythonTorchJAXTensorFlowSoftware EngineeringData AnalysisResearchCommunication

About the company

Point72 invests in multiple asset classes and strategies worldwide.

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
135H-1B approved
99%approval rate
30new H-1B hires
43PERM certified
$222,500median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202361
202472
20252
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202324
202417
202517
202625
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
202310
202412
202518
20263
Top sponsored roles
Quantitative Software DeveloperQuantitative Strategist, Macro TechnologyData AnalystIT Operations Engineer, Application SupportQuantitative Strategist, Treasury Quant Strategy
Sponsored employees from
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Job description

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.

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