1 year of C, C++, Linux experience
1-2 years of quantitative research, machine learning, or statistics using Python, Matlab, R.
Bachelors or above in the following fields: computer science, electrical engineering, financial mathematics, physics, statistics, applied mathematics.
Strong interest and motivation to generate market-beating returns.
Design and build quantitative alpha and strategies.
Run backtest and post trade analysis of strategies in production.
How to Apply
You are fascinated by financial markets and trading. You love reading papers, articles, and books about quantitative finance topics. You love the exciting of competing against other market participants and understanding the various agents in the market. You are excited by big data, machine learning, statistics, and applied mathematics.
As a quantitative trader, researching new strategy and alpha ideas will be a large part of your daily responsibilities. Each trader will be given a wide range of freedom to pursue his or her direction. The environment will be similar to academia in that you will consult many academic papers and textbooks to find inspiration for new ideas. Obviously, ideas that appear in published papers will not be profitable, otherwise they would be in papers in the first place, but they are usually a good starting point or source of new ideas. Here are some example papers for you to get a feel for the day-to-day research topics.
Traders will be offered extremely generous profit-sharing percentages of their strategy's trading revenue. If a trader is successful, this opportunity is tremendous upside potential.
Each trader has the opportunity to form a trading group within the firm. The trader will become the Team Lead, recruit his or her team members, manage the team's research and development directions, and decide compensation allocations to his or her team. This is an entrepreneurship opportunity to start a company within a larger company.