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Karkidi

Data Scientist - Intern

Karkidi, San Francisco, California, United States, 94199


About FaireFaire 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.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.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 is eager 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 and 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.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.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.We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business.We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand.

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