A/B Testing, Agile methodologies, Algorithms, Bayesian networks, Causal inference, Data science techniques, Database, Design of Experiment, Econometrics, Edge AI, Effective communication skills, Growth Analytics, Information Retrieval, Machine learning techniques, Marketplace, NumPy, Pandas, Product Development, Project management, Python Programming, Ranking, Recommendation Systems, Retail , SQL, Statistical modeling, Statistics, Terabyte scale datasets
About Faire
Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
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:
What it takes:
Faire’s flexible work model aims to meet the needs of our diverse employee community by making work more flexible, connected, and inclusive. Depending on the role and needs of the team, Faire employees have the flexibility to choose how they work–whether that’s mainly in the office, remotely, or a mix of both.
Roles that list only a country in the location are eligible for fully remote work in that country or in- office work at a Faire office in that country, provided employees are located in the registered country/province/state. Roles with only a city location are eligible for in-office or hybrid office work in that city. Our talent team will work with candidates to determine what locations and roles are eligible for each option.
Why you’ll love working at Faire
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.