Little Black Dresses, Stripey Tops, Machine Learning and Large Databases

Speakers

John Spicer and Paulo Sampaiologo

Abstract

EDITED is the industry standard tool used by fashion retailers like Topshop, Gap and Net-A-Porter to get pricing and product right.
Monitoring hundreds of retailers’ sites and ingesting 11M products every day poses a huge engineering challenge when it comes to processing data. And at EDITED, we deal with that challenge while working to ensure we’re also correctly classifying every product we see and extracting colour and category information, using complex data science models. And that's before it all has to be stored alongside our other 75M products and made searchable by our customers in under 500ms. We will discuss how EDITED works to solve big problems faced by the apparel industry while dealing with data science and processing challenges.

Bio Speaker

John Spicer is a Senior Software Engineer at EDITED. He works mainly on the backend but codes both in Python and Javascript. He has contributed to a huge variety of projects, including building search parsers for our customer facing application and data monitoring tools, as well as optimising our data querying infrastructure and processing pipelines. John formerly worked at Citigroup, coding mainly in C# and Java, before joining EDITED in early 2015. He has a BEng from Durham university and an MSc in Computer Science from Imperial, which he graduated from in 2012.

Paulo Sampaio leads EDITED's data science research and development, implementing a wide range of machine learning techniques that encompass methods, including natural language processing, computer vision, and deep learning with convolutional neural networks. He analyses text and image data types to extract meaningful attributes across our database of global retail data, to help solve fundamental problems faced by the apparel industry. Before working at EDITED, Paulo built revenue management algorithms for airlines in Brazil and worked as an analyst for Accenture. He has a Masters in Statistics and Operations research and a degree in Engineering.