Abstract: A significant part of a data science team’s value is determined by how effectively the rest of the organization leverages their work for strategy, planning and decision-making. But getting your findings to the right end-users involves far more than just effective analytic & modeling approaches to your work. This talk will discuss some of the lessons we’ve learned over the years at Greenhouse and share the most effective strategies we’ve employed to evangelize data science at the company. By the end of this talk, you will learn concrete recommendations to increase access and availability of data across your entire company.
Bio: Mona is a Data Science Manager at Greenhouse Software in New York City, where they contribute to data-informed decision making across the company and machine learning solutions to improve the hiring process for Greenhouse customers. They’ve previously worked in government, creating analytics and machine learning solutions to improve the lives of New Yorkers, and continue to be involved in civic projects through a number of volunteer and non-profit organizations. They’ve also been a statistics and data science educator with DataCamp, Emeritus, and in university settings. They hold a graduate degree in Developmental Psychology, and are passionate about contributing to the ethical use of data science methodology in the public and private sector.