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Data Scientist (Search)

Nextdoor

full-remoteseniorpermanentdata Full remote 121 days ago via WTTJ

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Tags

Machine LearningInformation RetrievalSearch RankingA/B TestingExperimentationSQLPythonNumPypandasscikit-learn

About the role

Role overview

Join Nextdoor as a Senior Data Scientist on the Search team. You will own the data science that powers the end-to-end search experience—helping neighbors find relevant people, places, posts, and businesses.

Responsibilities

  • Design and develop algorithms and models to improve search relevance, retrieval, and ranking.
  • Collaborate with cross-functional teams (product, design, engineering, marketing, operations) to support product development.
  • Produce and share strategic insights using data analysis, including:
    • Experiment design
    • Performance evaluation of ranking and search systems.

Requirements

  • Strong judgment to apply ML to real business problems and to define the right metrics for ranking/relevance.
  • Expert-level SQL and Python, with experience using common data science/scientific computing tools (e.g., NumPy, pandas, scikit-learn).
  • 5+ years of relevant Data Science experience.
  • Direct experience with Search, recommendations, or information retrieval products (query understanding, retrieval, ranking, relevance evaluation) and the associated metrics.
  • Strong experimentation skills, including designing and analyzing complex A/B tests, handling interaction effects, and measuring long-term metric movement.
  • Excellent communication skills (ability to synthesize and explain complex problems to varied audiences, including executives).
  • Experience designing, deploying, or monitoring ML production models.
  • Experience working with ranking algorithms for unstructured content.
  • Basic understanding of RAG systems.

Nice-to-haves

  • Not explicitly stated beyond the listed requirements (RAG understanding, unstructured ranking, ML production).

About Nextdoor

Nextdoor is a technology company that connects neighbors and communities through local posts, people, places, and businesses. It operates in the social networking and location-based services space, using data and machine learning to improve discovery and community experiences.

Scraped 6/11/2026