Data Scientist - Search & Recommendation
Canada
Applications have closed
Faire Wholesale, Inc.
About Faire
Faire is an online wholesale marketplace built on the belief that the future is local — there are over 2 million independent retailers in North America and Europe doing more than $2 trillion in revenue. 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.
Job Description: Data Scientist - Search & Recommendation, Machine Learning
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, recommendations, 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 member of Search for the Data Science team you’ll be responsible for developing machine learning-powered search 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 rankings? 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 and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. 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…
- You’ll be able to work on cutting-edge search query and understanding problems combining a wide variety of data about our retailers, brands and products
- You want to use machine learning to help local retailers and independent brands succeed
- You want to be a foundational team member of a fast growing company
- You like to solve challenging problems related to a two-sided marketplace
Qualifications
- 1 years of industry experience using machine learning to solve real-world problems, and a history of accomplishment and advancement in your Data Science career
- Experience with search/query processing for product development
- Strong programming skills
- An excitement and willingness to learn new tools and techniques
- Experience with relational databases and SQL
- The ability to contribute to team strategy and to lead model development without supervision
- Strong communication skills and the ability to work with others in a closely collaborative team environment
Great to Haves:
- Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
- Ability to quickly implement state of the art algorithms from an academic paper
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’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
- We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is an owner of the business and taking part in the founding process.
- We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
- We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.
- We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.
Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Salt Lake City, Atlanta, Toronto, London, New York, LA, and Sao Paulo. To learn more about Faire and our customers, you can read more on our blog.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing Computer Science E-commerce Engineering Machine Learning ML models PhD RDBMS SQL Statistics STEM
Perks/benefits: Career development Flex hours
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