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Data Science Intern - Personalization & Recommender Systems

FaireSan Francisco, CA
On-site Internship $75K/yr - $75K/yr

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Experience Level

Entry Level

Qualifications

Passion and strong interest in recommender systems and personalization. Experience with modern machine learning approaches, particularly in ranking and representation learning. For PhD candidates: a strong publication record in leading conferences (KDD, RecSys, ICML, NeurIPS, WWW, SIGIR). For Master’s candidates: notable research projects or relevant internships.

About the job

About Faire

Faire is an online wholesale marketplace focused on supporting independent retailers. By connecting small businesses with products from around the world, Faire aims to help local shops compete with major players like Walmart and Amazon. The company uses technology, data analytics, and machine learning to provide insights and tools that level the playing field for entrepreneurs everywhere.

Faire’s work strengthens local economies by enabling independent businesses to thrive. The team values resourcefulness, intelligence, and a commitment to community. Those who believe in supporting local businesses will find a shared purpose here.

Role Overview: Data Science Intern – Personalization & Recommender Systems

This internship focuses on building and improving machine learning systems that power search, personalization, and recommendations for Faire’s marketplace. Interns will join a team dedicated to developing algorithms that help local retailers discover relevant products and compete with larger competitors.

The team welcomes Master’s and PhD students with a background in recommender systems, personalization, or applied machine learning.

Who We’re Looking For

  • Strong interest in recommender systems and personalization
  • Experience applying modern machine learning techniques to ranking or representation learning
  • PhD candidates: a record of publications or submissions to top conferences (such as KDD, RecSys, ICML, NeurIPS, WWW, SIGIR)
  • Master’s candidates: meaningful research projects, internships, or open-source contributions in related areas

What You’ll Work On

  • Design and build advanced recommender systems for product ranking and discovery
  • Develop methods for user and item representation learning
  • Collaborate with machine learning engineers to move research solutions into production
  • Tackle personalization challenges that impact millions of recommendations each day

Location

San Francisco, CA

About Faire

Faire is at the forefront of revolutionizing wholesale trade by empowering local retailers with technology and data insights. Our commitment to small businesses fosters economic growth and competition against larger corporations.

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