Your responsibilities will include identifying areas where ML can create value for our customers, identifying the right ML framing of product problems, working with teammates and Product and Design stakeholders, conducting exploratory data analysis and research, deeply understanding the problem area, researching and identifying the right algorithms and tools, being pragmatic, but innovating right to the cutting-edge when needed, performing offline evaluation to gather evidence an algorithm will work, working with engineers to bring prototypes to production, planning, measuring & socializing learnings to inform iteration, and partnering deeply with the rest of team, and others, to build excellent ML products.

To be successful in this role, you will need to have broad applied machine learning knowledge, 3-5 years applied ML experience, practical stats knowledge (experiment design, dealing with confounding etc), intermediate programming skills, strong communication skills, both within engineering teams and across disciplines, comfort with ambiguity, typically have advanced education in ML or related field (e.g. MSc), and scientific thinking skills. Bonus skills and attributes include track record shipping ML products, PhD or other experience in a research environment, deep experience in an applicable ML area. e.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering, strong stats or math background, visualization, data skills, SQL, matplotlib, etc.

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