Quantitative Researcher - Machine Learning

the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. Requirements: PhD or PhD candidate in machine learning, computer science, statistics, or a related field Experience with sequential modeling and time series forecasting using deep learning Experience with deep neural networks and representation learning Prior experience working in a data driven research environment Experience with translating mathematical models and algorithms into code Proficient in programming languages such as Python and R Experience with machine learning software libraries such as TensorFlow or PyTorch Experience with natural language processing technology a strong plus Excellent analytical skills, with strong attention to detail Interest in applying machine learning to finance Collaborative mindset with strong independent research ability Strong written and verbal communication skills We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we’d love to learn more about what excites you.