Degree in Computer Engineering
Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming
Faire is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced data scientists and machine learning engineers are developing solutions related to discovery, ranking, search, recommender systems, logistics, underwriting, and more - all with the goal of helping local retail thrive.
The Data Science team owns a wide variety of algorithms and models that power the marketplace. We care about building machine learning models that help our customers thrive.
As a Senior Data Scientist - Machine Learning on the Personalization team you’ll be responsible for developing machine learning-powered ranking models and adding personalization to our search and discovery. You’ll determine answers to questions like, how relevant is this product to this retailer and how can we infer that in real-time? Can we create real-time embeddings of users' interests and use them to power ranking? How can we improve purchase flow? What techniques can we use to enable our A/B tests to more quickly converge when dealing with low sample sizes?
Our team already includes experienced Data Scientists from Square, Quora, TripAdvisor, Instacart, and TripAdvisor; and the head of the team is an experienced manager from Airbnb who is also a professor of machine learning at UC Berkeley. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there!
You’re excited about this role because…
Great to Haves:
What We Offer:
Faire is an online wholesale marketplace built on the belief that the future is local. There are over 1M independent retailers across North America alone doing more than twice the revenue of Walmart and Amazon combined. At Faire, we're using the power of tech, data, and machine learning to connect a thriving community of over 150,000 brands and independent retailers around the world. Picture your favorite boutique in town.
Toronto, ON, Canada