Point72 / Cubist
Quantitative Researcher Intern
Eligibility
- Candidate must be a Masters or PhD student in quantitative discipline
Internship for Masters or PhD candidates in quantitative disciplines to conduct research on scalable equity trading signals using machine learning and large data sets.
Responsibilities
- Conducting full pipeline signal research, from ideation, via implementation and backtesting, to eventual application
- Adapting and extending existing results in machine learning and conducting novel research
- Analyzing very large data sets to extract features useful for predictive models
- Providing research assistance to the team
- Helping improve the team’s research infrastructure
Requirements
- Masters or PhD candidates in machine learning, computer science, finance, mathematics, or other quantitative disciplines
- Demonstrated ability to conduct independent research utilizing machine learning over large, possibly noisy, data sets
- Strong analytical and quantitative skills, and detail-oriented mindset
- Proficient in Python or C++, and Linux environment
- Excellent written and verbal communication skills
- Willing to take ownership of his/her work, working independently and within a collaborative team
- Commitment to the highest ethical standards
Skills
- Python
- C++
- Machine Learning
- Data Analysis
- Research
- Linux
- Employer posted
- Last checked