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 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:

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

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

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. 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 Accommodation Request Form (https://bit.ly/faire-form)

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

Job Description

About Faire

Similar Jobs

Fraud Strategy Lead

Senior Fullstack Ads Engineer