Staff Data Scientist / Machine Learning Engineer – Ads Full-time

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, but individually, they are small compared to these massive entities. 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.

About this Role:

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, ads, logistics, underwriting, and more – all with the goal of helping local retail thrive.

As a member of the Discovery Data team you’ll be responsible for:

• Ads / Sponsored Products: Joining a newly established team building Ads Delivery and Advertiser Optimization from the ground up and tackling challenges in ads targeting, retrieval, prediction/ranking, bidding, pacing, and auction design.

Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, LinkedIn and Pinterest. We’re a lean, talented team with high opportunity for direct product impact and ownership.

You’re excited about this role because…

• You’ll be able to work on cutting-edge search / personalization / ads 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

• Experience with leading cross-team and cross-functional technical strategy and roadmap, solving long-term open-ended problems, and consistently driving significant business impact for the whole org.
• 5+ years of industry experience using machine learning to solve real-world problems
• Experience and strong understanding of search / personalization / ads for product development
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• Experience with deep learning
• 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

Salary Range:

Canada: the pay range for this role is $184,000 to $253,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future

This role will be in-office on a hybrid schedule – Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays, effective the week of January 13, 2025. Additionally, in-office roles will have the flexibility to work remotely up to 4 weeks per year.

Applications for this position will be accepted for a minimum of 30 days from the posting date.

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 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 Toronto, London, and New York. 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.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form)