ONLINE: Data Science applied in e-commerce

Follow vpTech in live on Youtube with one e-meetup per week!
Despite of confinement, let's keep sharing our experiences, successes, failures and feedbacks!
Talks done by our tech experts all over in Europe!

Here is the link:
https://youtu.be/hzvcQBCohLM

3 topics

1. A/B TEST, By Betty Moreschini

Like a lot of major websites, at Veepee we use A/B tests to improve the design of the site. A few years ago we decided to switch to a custom, homemade, A/B test engine. On this journey we learned a lot of valuable lessons about A/B testing, and we’ll share them with you on this talk.

About Betty: Data Engineer at Veepee in Paris, where she has worked on recommender systems and A/B Testing. She is now working on demand forecast.

2) DEEP RANKER, by Amine Zghal

With the rise of Youtube, Netflix and Amazon, recommender systems which consist of putting forward the right items to the right person have become a strong competitive tool for tech companies.
As one of the European leaders in e-commerce, Veepee focuses in increasing its quality of offer regarding members tastes and cravings.
Motivated by improving the web site's overall conversion rate, Veepee has invested in a strong data department which has decided to put in place a home-made recommender system that would fit exactly Veepee's special needs and constraints. Throughout this talk we will explore several classic personalisation approaches and how they behave under Veepee's business model constraints. Then we will present the recommender system we built based on triplet loss and siamese neural nets. Finally, we'll observe how our model behaves in production and have a look at the latest performances.

About Amine: Data scientist at Veepee (https://www.veepee.fr/). As part of the data organisation, I work on recommender systems for Veepee's home page and CRM. I also teach the streaming algorithms course at Télécom SudParis.

3) PRODUCT RANKING, by Joel Quesada

Have you ever wondered how Veepee uses data to provide optimal product rankings? How do you decide what products go on top and which ones on the bottom? Join us and you will discover this and more!

About Joel: Data Scientist at Veepee
Background: BSc in Computer Science & MSc in Artificial Intelligence.
Level of experience: +4 years working in AI & Data topics: image classification, natural language processing, optimization problems, etc.
Mission at vpTech: provide and implement data-driven solutions to different problems such as product ranking, sales forecasting, pricing optimization, etc.

vpTech

vpTech, the Veepee Tech community, is one of the biggest in the retail industry in Europe. The team handles more than 50 tools to support the business and the growth of Veepee (e.g., React, C#, Haskell, Python, Cassandra, Couchbase, MongoDB, and Kubernetes…)!

Based in Paris, Lyon, Nantes, Nice, Amsterdam, Warsaw, Barcelona, Sevilla, Brussels, Lausanne and Tel Aviv, we advocate for flexible, autonomous and multicultural feature teams.