Quantitative Researcher: Machine Learning / Deep Learning
· Apply machine learning or deep learning methods to develop sophisticated prediction models and build rigorous evaluation systems;
· Keep up with the most recent developments in machine learning;
· Develop new neural networks and machine learning models to adapt to financial data.
· Bachelor’s /Master’s /PhD degree in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science, IEOR, or a related field from top universities;
· Solid math foundation, deep understanding of machine learning and deep learning, experience in applying machine learning to real-world data-sets, such as financial time series, natural language processing, image recognition and other areas;
· Advanced skills in at least one programming language (like C, C++, Java, or Python). Proficiency in machine learning frameworks, e.g. TensorFlow / PyTorch;
· Publications in related journals (e.g., NIPS, ICML, CVPR, COLT);
· Participants in Kaggle, KDD, Numerai are preferable;
· Fast learner with strong communication skills and logical thinking, strong sense of responsibility, and self-driven working habit;
· Proficiency in Mandarin is a plus.