Data mining and predictive analytics at an online luxury fashion retailer - ON-109

Preferred Disciplines and Level: Computer science, Data science, Math, Statistics or Fashion or Retail Technology; Masters
Company: The September
Project Length: 8-12 months (2 units)
Desired start date: As soon as possible
Location: 535 Queen Street E Toronto
No. of Positions: 1
Preferences: Toronto preferred, but will consider applicants outside this area. Language: English

About the Company: 

The September is Canada’s first online luxury retailer. The September is a women’s e-commerce business that makes it easier for Canadians to access luxury items. We retail shoes, the fashion item women love more than any other. We make the experience engaging, with compelling, magazine-style content that reflects a luxury lifestyle, while providing unparalleled high-touch service.  

Project Description:

We are offering an exciting opportunity to join a fashion e-commerce team at the early phase of the business. We are looking for interns who are genuinely interested in participating in the dynamic, and sometimes unpredictable world of a fashion start up.  

It is a chance to dip your toe into both the retail and data science aspects of the business.

We are looking for a Data Scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver an exceptional digital shopping experience. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. With this information and toolset, you will then be able to create and implement a unique algorithm in an effort to create a personalized shopping experience for every visitor.

Research Objectives:​

  • Identify and apply data mining approaches to select, extract, and analyse critical data from existing company database, as well as external sources if necessary
    • Enhancing data collection procedures to include information that is relevant for building analytic systems
    • Create automated anomaly detection systems and track their performance
    • Create an algorithm to deliver a personalized shopping user experience for each visitor to the site based on data and predictive analytics

Methodology:

  • To be determined

Expertise and Skills Needed:

    • Experience in data mining and data visualization
    • Coding expertise
    • Interest in retail and/or fashion would be ideal

     

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects.

    2. Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed.

    Program: