Speaker "Alexander Smith" Details Back



Predicting Employee Turnover: A Machine Learning Approach


The cost of employee turnover is high across all industries, so it’s not surprising that leaders are increasingly using data to inform their employee retention strategies. At Limeade, we use machine learning technology and data not typically leveraged by human resource (HR) departments to predict potential employee attrition and identify business units at risk of increased turnover. Our approach enables leaders to focus their efforts and create data-driven retention strategies that go beyond traditional HR approaches and elevate a company’s culture. This presentation will cover our method and application of machine learning to alleviate employee turnover proactively in large organizations.


Alexander Smith manages the Data Science team at Limeade, a well-being and engagement company focused on elevating the culture of its customers. With his team, Alex works on a wide variety of data science problems related to improving company cultures and changing behaviors, working on everything from analytics and dashboards to machine learning and cognitive AI solutions. Alex started his career in data as a data analyst with FlowEnergy, a startup focused on applying machine learning to industrial HVAC systems, before establishing the company’s data science team. Prior to Limeade, Alex worked with AIM Consulting as a Solutions Consultant focused on data engineering and data science, working with a variety of companies in the Seattle area like Microsoft and Expedia. Alex is a strong proponent for data science and machine learning, and has spoken at several conferences and tech talks all around the Seattle area, evangelizing the power of data and data science while seeking opportunities to mentor and coach others in the field. He earned his B.S. in Economics from Washington State University.