Data Scientist

Found in: Jooble CA O C2 - 1 week ago


Canada Faire Full time

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for search, personalization, recommender systems, and ranking. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.
At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
We have a few openings in the Search & Recommendation organization available
Search/Discovery Team: Experience with search/query processing for product development preferred.
Recommendation/Browsing Team: Experience with personalization, ranking, and recommendation preferred. You will be able to work in a cross-functional setup on core Machine Learning problems. The areas you might be working on include content-based recommendations, personalized retrieval and ranking, user signals building, etc.
We're looking for someone with experience working on projects related to the fields above and who are eager to wake up ready to take a problem end-to-end, dive into our information-rich databases, and produce actionable insights.
Our internships are paid and 12-to-14 weeks in duration. We have flexible start dates and are open to extending internship durations based on need and mutual fit.
What you will be doing:
Define, plan and execute cutting-edge machine learning or other new algorithms that will be a/b tested with guidance from a manager or technical lead
Communicate project objectives and results clearly, both within the group as well as to the broader team
Tackle complex issues inherent in managing a two-sided marketplace. Your ability to identify and address these challenges will be critical to our continued growth and success
What it takes:
We are open to currently enrolled Master’s & PhD students and recent Master’s & PhD graduates, who have an academic focus in Computer Science, Operations Research, Statistics, Econometrics or a related technical field
Hands on experience with real datasets and familiarity using python, sklearn, numpy, pandas, and SQL
Familiarity with various machine learning techniques and statistical methodologies (Bayesian methods, experimental design, causal inference)
A track record of developing end-to-end Data Science projects and/or producing academic papers that have been showcased in top journals or conferences
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