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·        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