About your role
- Participate actively in all aspects of quantitative trading and research, including strategy design and implementation, back testing, machine learning based recommendation models, live trading analysis and data collection and clean-up etc.
- Your role will evolve over time based on business growth and your own development progress;
About your background
- Excellent academic record of bachelor's degree (or above) from a top university, major in Computer Science, engineering or other quantitative related discipline;
- A PhD//Master from a strong program that focuses on Machine Learning/Data Science/Computer Science/Physics/Mathematics/Statistics is an advantage;
- You have demonstrated achievements in computer programming and mathematical modelling, for example you have win awards in mathematical modelling and programming contest, i.e. top stars Github repo, publication in industry leading journals and conference papers etc;
- Practical mastery of key ML techniques
- Independent research experience;
- Highly motivated and competitive;
- Learning curiosity & agility;
- A good communicator and team player.
Complementary Skills
- A deep understanding of feature engineering, and the problems of bias in data-sets; preferably with Kaggle track record
- Additional experience with time series modelling techniques an advantage.
- Experience working with large datasets, tick data experience highly regarded
- Experience building mathematical models for complex real-world problems
Programming Skills
- Python
- R (or Matlab/Octave)
- C++ experience an advantage (or equivalent OO programming language such as C# or Java)
- q/KDB experience an advantage
Your opportunities
- Stay ahead of market with latest technology & knowledge sharing
- Senior Partner one-on-one mentorship
- Highly competitive compensation package
- Work in a flat structure where your talent gets noticed and promoted quickly
- Work with like-minded people who share the common value of being highly motivated, meticulous in details, and systematic thinking.