Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Kaylea Haynes

Kaylea Haynes
Data Scientist , Peak

Website

Kaylea Haynes is a data scientist at Manchester-based data analytics service Peak, which helps companies grow revenue and profits using data and machine learning. Kaylea focuses on developing techniques for demand forecasting. She is a member of the Royal Statistical Society and co-organizes R Ladies Manchester. Kaylea holds a PhD in statistics and operational research from Lancaster University. Her thesis was titled “Detecting Abrupt Changes in Big Data.”

Sessions

14:05–14:45 Thursday, 24 May 2018
The ins and outs of forecasting in a hire business
Data science and machine learning, Data-driven business management
 Location: Capital Suite 12 Level: Beginner
Kaylea Haynes (Peak )
Deciding how much stock to hold is a challenge for hire businesses. There is a fine balance between holding enough stock to fulfill hires and not holding too much stock so that overall utilization is too low to achieve the return on investment. Kaylea Haynes shares a case study on forecasting the demand for thousands of assets across multiple locations. Read more.