Job listing

Machine Learning – High Frequency Trading

  • Data science and statistical research

One of, if not, the fastest High Frequency Trading firms in the world are currently hiring Machine Learning focused researchers to join a high performing team in New York. They invest heavily in technology and personnel possessing state-of-the-art AI and compete with the likes of Google, Facebook and Apple when hiring the top PhD’s from the top schools in the world.Although a Finance company, they position themselves more as a tech house who trades and the culture reflects this.

There are teams in New York and Chicago are heavily focused on Machine Learning/Deep Learning Research using these techniques to predict Financial Markets and capitalize on trading opportunities. Previous Finance experience is not required, in fact, they prefer those from outside of industry who can bring alternative ideas to their successful team. In particular, they are interested in the techniques behind Computer Vision and NLP.

The successful candidate will have:
• A PhD from a top academic institute in a quantitative subject – Computer Science, Maths, Statistics, Physics, Computational Physics/Biology etc
• One-year experience in a professional environment
• Strong programming skills with Python and/or C++. Both would be preferable
• Close to the academic community – publications in top journals and at reputable conferences (NIPS, ICML etc.)
• Track record of achievements outside of academia – Math Olympiads, top performers in Machine Learning/Deep Learning competitions
• Strong grounding in Statistics

Machine Learning in Finance is usually faster and more dynamic than your usual tech houses; Financial Markets move quickly and are forever changing. Intellectually, it is a very interesting problem providing a great challenge to the right candidates.

Key Words
Machine Learning, Deep Learning, Neural Networks, Reinforcement Learning, Computer Vision, NLP, Bayesian Statistics, Supervised Learning, Unsupervised Learning, Algorithmic Trading, High Frequency Trading


New York, Chicago, London


Very competitive