Data Scientist - Client Platform

Discord•San Francisco, CA
•$160,000 - $200,000•Onsite

About The Position

Discord is looking for a Data Scientist to join their Client Platform Data Science team. This role will focus on ensuring the Discord platform functions smoothly, partnering with teams responsible for designing, building, and supporting Discord. The Data Scientist will work on improving app performance, enhancing user experience, and driving growth. The role involves strategic analyses, experimentation, and dashboarding, with a specific focus on improving the reliability of Discord's mobile and desktop applications through advanced metrics, monitoring, and automation. The company is seeking individuals passionate about data and making a significant impact.

Requirements

  • 2+ years of hands-on analytics experience turning ambiguous business problems into clear, actionable insights
  • Experience designing, analyzing, and interpreting A/B tests at scale
  • Strong SQL skills and experience building clean, performant dashboards (Tableau, Looker, or similar)
  • Clear communication skills, with the ability to make complex findings easy to understand
  • Curiosity, a collaborative attitude, and a drive to solve hard problems

Nice To Haves

  • Passion for Discord or online communities
  • Experience with performance/reliability analytics for online services
  • Familiarity with social or subscription products (social graphs, LTV, funnel analysis)
  • Production ETL or BigQuery experience
  • Experience using AI in data science work

Responsibilities

  • Partner with teams throughout Discord through the full analytics lifecycle - from exploratory analyses to dashboards, reports, and A/B testing
  • Define KPIs and diagnostic metrics that improve the user experience, and build dashboards to make them timely and actionable
  • Build custom datasets to monitor novel product features and processes
  • Share insights with technical and non-technical audiences, and iterate based on feedback
  • Champion A/B testing best practices - helping teams design, analyze, and interpret experiments correctly
  • Collaborate with data and engineering teams to design scalable and future-proof instrumentation and self-serve tooling

Benefits

  • equity
  • benefits
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