· Build data pipelines for machine learning experiments, research, and production (where machine learning models are used for trading signals)
· Measure, track, and visualize metrics on holdout test sets.
· Debug and examine model outputs qualitatively, to understand why some methods work better than others, even with limited testing data.
· Master’s or PhD candidate in computer science, or related disciplines
· Proficient in scikit-learn and either Tensorflow or PyTorch
· Experience with deep learning techniques
· Experience with machine learning on graphs, time series, and financial data (preferred)
· Interest in applying machine learning to finance
· Experience with AWS a plus
· Willingness to take ownership of a project, working both independently and within a small team