You will be contributing to our core library by implementing analytics in python.

Requirements: Keen on research with high real-world impact. Expert in understanding machine learning techniques (Reinforcement Learning, Transfer Learning, GANs, NLP, Bayesian Methods). Hands-on experience in ML libraries (TensorFlow, PyTorch, NLTK, Gensim, Scikit-Learn). Proficient in Python programming. Ability to create high quality code.

Degree: PhD (candidate or completed) with a focus on deep learning

Useful Experience: Software engineering skills, Visualization in Bokeh, Web applications, Cloud computing, Prior exposure to Finance or Energy

Quant R&amp;D

Quant R&D