Cubist Quantitative Researcher
Requirements at a glance
Cubist Quantitative Researcher at Point72 is a role based in Hong Kong. The posting asks for 2+ years of experience and a bachelor's degree. It does not mention visa sponsorship. Key skills include Python, Machine learning, and pandas. Applications are submitted through Greenhouse.
- Experience
- 2+ years
- Education
- Bachelor's degree
- Visa sponsorship
- Not mentioned in the posting
- Application platform
- Greenhouse
Skills in this posting
- Python
- Machine learning
- pandas
Extracted automatically from the job description. Confirm details in the full posting below.
ABOUT CUBIST
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
ROLE
The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance.
RESPONSIBILITIES
- Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas.
- Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization.
- Maintaining and improving portfolio trading in production environments.
REQUIREMENTS
- Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline.
- 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus.
- Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning.
- Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas.
- Ability to work both independently and collaboratively within a team.
- Commitment to the highest ethical standards.