This role will require the candidates to have expert hands-on Python programming skills as well as excellent knowledge in machine-learning and statistics. Master of Finance with relevant data science/analytics/machine-learning/quantitative internship experience are welcome to apply.

Responsibilities

•Use large data sets to create trading strategies, improve trading, quantitative research and data mining

•Collaborate with quants and traders to develop and improve trading strategies

•Monitor development of new and existing data sets

•Use machine-learning to improve existing models with new learning algorithms, alternative feature transformations, feature selection techniques, improved evaluation metrics, and increased model diversity

Requirements

•PhD in Finance with good knowledge in Statistics or Physics or Applied Mathematics and Computer Science/Machine Learning, or other highly quantitative field (or related subject)

•Expert experience in hands on Python development (Numpy / Pandas / Scipy)

•Experience with C++

•Experience with machine learning libraries (scikit-learn, keras, tensorflow, ...)

•Self-starter that is able to run projects independently

•Working knowledge of forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks or support vector machines

•Capable of managing large data sets and developing statistical models

•Good analytical and synthetic mind