Quantitative Researcher

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.

This collaborative, and entrepreneurial systematic investment team is seeking a strong quantitative researcher to join in developing new signals and strategies. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.

• Working on alpha research, with a primary focus on: idea generation, data gathering and research/analysis, model implementation and backtesting for strategies.
• Combine rigorous scientific methods and machine learning or statistical learning techniques to explore, analyse, and harness a large variety of datasets in order to build strong predictive models which will be deployed to the investment process.
• Develop and improve sophisticated python-based software tools and libraries for statistical and machine learning researches.

Preferred Technical Skills

• Strong research and programming skills in Python and experience working on sophisticated Python-based software tools and libraries in a fast changing environment.
• Masters degree in a quantitative subject such as Computer Science, Applied Mathematics, Statistics, or related fields from a top ranked university.
• Demonstrate excellent communication, analytical and quantitative skills.