How would you rank your products within a category to increase customer satisfaction and generate sales? How about ranking search results? Would your ranking create more revenue than someone else’s?

WDSS is recruiting for a candidate to work together with our Research sponsor—Walgreens Boots Aliance, on a hands-on project in e-commerce product ranking.

In this project you will be working on creating a process to optimise product ranking on the boots.com website. The process can be rule-based or learning based; different or similar to other website’s ranking, session based or customer based, or a combination of all of the above; the choice is entirely yours. You will have the opportunity to test your ranking against other rankings in a real-world scenario.

• Research novel solutions for intelligent search engines and product rankings.
• Propose a ranking method, either rule based or machine learning based, and score the methods against sample data
• Meet regularily with Boots data scientists to share and discuss ideas
• Summarise the result of your work in form of a blog post

• Knowledge of programming languages (preferably Python).
• Strong data-wrangling skills
• Ability to work independently
• Motivation to research cutting-edge data science solutions.
• [Preferable] Experience with machine learning.

• Use the application button on this page or email recruitment@wdss.io.
• The body of your application should contain one short paragraph for each of the following points:
  • Why you wish to take up the role
  • How you are qualified for the role
• Please attach your CV / Resume together with your application
• We will promptly get in touch to discuss the role further.