About this role:
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 Data organization available
Search: Experience working with GenAI and LLMs for search optimization, query understanding, retrieval and ranking.
Personalization: Experience with personalizing recommendation surfaces through embeddings, near-real-time streaming signals, explore-exploit and diversification.
Retailer Growth: Experience developing machine learning solutions to drive growth through paid marketing bidding, targeting efficiency and sitemap optimization preferred.
Retailer Products: Experience with predictive modeling, Redshift and Mode Analytics preferred
We're looking for folks 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:
What it takes:
Pay rate:
Canada: the pay rate for this role is $60 CAD per hour.
San Francisco: the pay rate for this role is $75 USD per hour.
Actual hourly pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The pay range provided is subject to change and may be modified in the future.
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
This job posting is for an existing vacancy.
#LI-DNI
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Why you’ll love working at Faire
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Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our (
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s
Data Science Intern • Kitchener-Waterloo, ON; San Francisco, CA; Toronto, ON