Bachelor's degree in a technical area such as computer science or engineering
Required Experience & Skills
Advanced quantitative, research and statistical skills with a tenacity to create or find a powerful, sophisticated strategy and solution at a medium to high frequency
Aptitude and experience in developing, monetizing, and evolving high frequency algorithms
Extremely analytical and probabilistic mindset with superb problem solving skills
Confident vision of building and leading teams driven to compete and win
Motivation and resourcefulness in quickly solving hard problems through the creative application of technology
Ability to manage numerous trading development priorities with ease
Ability to facilitate collaboration with team members and other departments in order to drive productivity
Values teamwork and is capable of thinking independently
Ability to generate trading ideas and design overall strategies at a high level using the tools available
Willing to learn the intricacies of a world-class high-frequency trading floor environment and know how to contribute in a meaningful manner
Ability to adapt to challenging and changing situations
Strong mathematical aptitude and entrepreneurial mind
Programming proficiency in C++ and/or Python
Working knowledge of TensorFlow and Pytorch is a plus
Experience with Slurm or another distributed compute cluster environment
Excellent verbal communication including during under pressure situations
3-5+ years working experience in high volume electronic / systematic / high frequency trading
Outstanding and consistent Return on Capital (ROC)
Familiarity with numerous trades in areas such as equities, treasuries, metals, ETFs, futures, or options
Demonstrated the ability to use sound judgment and maturity while trading and managing a large risk capital book
Knowledge of generating trades from data driven analysis
Experience holding team members accountable for driving results
Experience back testing strategies including microstructure research
Practical experience in applying advanced machine learning techniques to trading problems
Employee must be an EU citizen
Employee must live in or be in daily commuting distance to Amsterdam
