We are looking for a Quantitative Trader to join our Quantitative Trading team in our Amsterdam office. As a firm, we are at the intersection of scientific research, finance, and cutting edge technology. Financial markets have made a rapid shift from trading in the pit towards algorithmic trading, and our firm has developed into a FinTech company.
Our new Quantitative Trader will be responsible for developing trading strategies from scratch. Therefore, we expect you to be innovative, analytical, hands on and have a winning mentality. You will come up with your own trading ideas who will be profitable for Flow and you will receive the full support you need to develop this strategy. Thereafter, you will be monitor your own trading strategies in real-life to see how successful it is.
A Day in the Life
Start up systems and check on the latest news and market movements.
Stand up meeting trading: analysts give a briefing on the latest market developments and figures of the day, an IT operations representative briefs on the health of our systems: all systems are good!
08:30 – 9:30
A new developed strategy based on a curve model is live at another trading desk. I check if the setup is correct and if the model behaves correctly. Since the model is in a deployment phase it is very important to monitor the behavior of the strategy until someone else can fully takeover. I keep monitoring the strategy until 09:30.
09:30 – 12:00
Back at my own desk. I analyze last weeks data in Python while monitoring the behavior of the curve model on the site. Discuss the model with a fellow quant trader to see where we can improve.
Grab some lunch and eat it at my desk.
12:30 – 14:00
On my way to the training room. Today I am going to teach a group of junior traders how to implement a model as a new strategy in our trading platform.
14:00 – 15:00
Discus latest developments and planning with a development team.
Sync on the behavior of the curve model strategy.
Testing another new strategy in the simulation environment. This model is not ready for production yet but the results look promising. Most likely it is ready to run in production at my desk next week.
Monitor the curve model until markets close.
Back at my desk. Do some java coding to improve the curve model.
- Develop trading strategies from scratch (eg: relative value) for our financial products;
- Apply AI and Machine learning techniques (e.g. deep neural networks);
- Manage your own trading book;
- Work in close collaboration with our Software Developers, Quant Researches and Traders;
- Back-testing and optimize models;
- University degree in engineering, physics, math, statistics, computer science (or similar) or PHD and a demonstrable interest in trading;
- Interest in Machine Learning Techniques and AI, experience is an advantage;
- Experience with a scientific programming language (C, C++, Python, JAVA, or similar);
- Strong mathematical and statistical skills;
- Ability to reason logically, deliver under pressure and take ownership;
- Ability to spot opportunities, innovative and creative;
- Competitive attitude, eager to learn, proactive and able to work in a team;
- Maximum of three years’ work experience
- Excellent verbal and written English skills.
- Recruitment Process / onboarding
- As we do not expect you to have any trading knowledge upfront, we offer you an extensive onboarding program. Within two months, you will learn about our core business, the financial products we trade, and the mathematics required for pricing them. You will go through quantitative and trading classes given by our senior Quants and Traders. Finally, you will finish your onboarding program with a co-project with Junior Traders.
Please apply through our website with a CV and convincing cover letter. You will need to pass our IQ test and numerical test to be invited for the technical interview. During the recruitment process, you will meet several people from the Quant and Trading teams who will test your problem solving skills and your mathematics background. Up for a real Quant Trading challenge? Apply now!