Point72
Quantitative Researcher – Machine Learning
Join to apply for the
Quantitative Researcher – Machine Learning
role at
Point72 Quantitative Researcher – Machine Learning
Join to apply for the
Quantitative Researcher – Machine Learning
role at
Point72 Get AI-powered advice on this job and more exclusive features. 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.
The annual base salary range for this role is $150,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. Seniority level
Seniority level Entry level Employment type
Employment type Full-time Job function
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Join to apply for the
Quantitative Researcher – Machine Learning
role at
Point72 Quantitative Researcher – Machine Learning
Join to apply for the
Quantitative Researcher – Machine Learning
role at
Point72 Get AI-powered advice on this job and more exclusive features. 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.
The annual base salary range for this role is $150,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. Seniority level
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