| The ideal candidate will have • 3-5 years hands-on experience building predictive models, recommendation systems, or NLP/text mining tools. • Familiar with the foundational approaches to the major data science disciplines, such as data preparation, advanced statistics, machine learning, simulation, and natural language processing • Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies • Connections to the recommendations and / or information retrieval academic community • Experience and proficiency with various programming languages (e.g., Python), machine learning tools (e.g., scikit-learn), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databass (e.g., MongoDB, graph database), Linux and shell scripting • Masters in a quantitative research field (e.g., Computer Science, Electrical Engineering, Applied Mathematics, Physics, etc.). PhD preferred. • Ability to work in a culture that thrives on feedback and seeks opportunities to stretch outside comfort zone • Bias for action and completion |