✦ Luna Orbit — Data & Analytics

Senior Data Scientist

at Intercom

📍 London, England Onsite Posted April 01, 2026
Type Full-Time
Experience senior
Exp. Years 5+ years
Education Not specified
Category Data & Analytics

Senior Data Scientist in Intercom's RAD team drives data-informed decision making by partnering with product teams, designing and building end-to-end data pipelines, and delivering scalable self-serve insights.

  • Partner with product teams to define questions and metrics; build end-to-end data pipelines; develop product success metrics; shape semantic layers and self-serve interfaces; craft data stories for across R&D and broader company

Focus on analytics, data pipelines, and data products; uses SQL, Python, statistics; leverages AI-assisted tooling to accelerate analysis and storytelling; works with product managers, designers, and engineers.

The ideal candidate has 5+ years of data experience, strong SQL and statistics background, and a track record building data pipelines and self-serve analytics to influence product decisions.

5+ years experience working with data to solve problemsStrong SQL skillsSolid grounding in statisticsExperience with data pipelines
Product analyticsAI-assisted toolingSemantic layersData storytelling
5+ years experience with data; strong SQL; statistics; data pipelines; self-serve insights; data storytelling; dashboards; Python; AI-assisted tools (Claude CodeCursor)
SQLstatisticsdata pipelinessemantic layersPythonAI-assisted toolsClaude CodeCursordashboardsself-serve insights
communicationstorytellingownershipcuriositycollaboration
Industry SaaS
Job Function Deliver data-driven insights and scalable data products to inform Intercom's product and R&D decisions.
Role Subtype Senior Data Scientist
Tech Domains SQL / PostgreSQL, Python, Machine Learning
Senior Data ScientistData ScientistSQLstatisticsdata pipelinesself-serve insightsdata storytellingdashboardsproduct analyticsAI-assisted toolsClaude CodeCursorPythonsemanticssemantic layersIntercom RADLondon

Less than 5 years of data experience, Weak SQL or statistics background, No experience building data pipelines

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