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  • Data Scientist - Intern Toronto
  • Faire in Toronto, , Canada
  • jobs
  • 1 month ago

jobs description

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 multiple openings on the following teams available:

Retailer Growth Team - Activation: Experience with signal extraction, entity resolution or confidence-score models preferred.

Brand Team - Listing Quality: Experience with computer vision preferred.

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 12-14 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
Toronto ON

salary-criteria

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