Data Science Intern
Company: Faire
Location: San Francisco
Posted on: April 1, 2026
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Job Description:
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: 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 Privacy Notice (https://www.faire.com/privacy)
Keywords: Faire, Salinas , Data Science Intern, Engineering , San Francisco, California