Requirements

Either a post-graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms. Exceptional candidates with a proven record in data science competitions also considered
Experience in deep learning, reinforcement learning, optimization, Bayesian methods, NLP, or approximate inference
Strong reasoning and mathematical skills to develop custom models
Proficiency in Python, Scikit-Learn, NumPy, Pandas, and Jupyter Notebooks, with knowledge of object-oriented programming
Previous publications at conferences like NeurIPS, ICML, or ICLR

What You'll Be Doing

Disproving the efficient market hypothesis daily using cutting-edge ML techniques
Developing and testing ideas with real-world data in an academic research environment
Reading and discussing the latest publications in ML within a collaborative research community
Attending conferences worldwide such as NeurIPS, ICML, and more