Script Scores and back again - A tale of merchandising algorithms in Elasticsearch

This talk is about the flexibility and performance of painless scripting in Elasticsearch. That flexibility brought big wins to the business at SimpleTire and it continues to do so by being easily adaptable as new merchandising insights are discovered.

This story has 4 chapters: 1) Inherited a multi-objective ranking model that was built via an ETL job and stored in SQL for index time inclusion. 2) Tasked with migrating the algorithm into Elastic for real time scoring. 3) Solved using Painless scripting for maximum flex-ability and extend-ability for the future. 4) Long term wins: a-b testing easiness, weighting adjustments, bottom line value, rescoring for personalization

This talk is generally valuable to any e-commerce team because it walks through the process of converting business logic into search logic, all with an eye on improving the bottom line.

Nate Day

Open Source Connections

Nathan has always been interested in how technology can improve the human experience. He was drawn to study biotechnology in college, where he worked to research protein localization in plants and to build open-source software to model bacteriophage genomes. After graduating he joined a start-up drug development company focused on building better translational disease models. There he worked on the technical challenges of building multi-dimensional tissue systems and helped successfully develop first in class tumor and liver disease systems. From there he joined the computational biology group were he focused on building reproducible analysis pipelines and front-ends for exploring high-dimensional data. He is excited to bring his R&D experience and analytics expertise to the challenging problems of search relevance.