Senior Data Scientist

Intercom Intercom · Enterprise · London, United Kingdom · R&D

This role is for a Senior Data Scientist at Intercom, focusing on using data and insights to drive decision-making within the Research, Analytics & Data Science (RAD) team. The role involves partnering with product teams to identify and answer key questions using data, developing product success metrics, designing and updating data pipelines, and influencing product strategy through analysis. While the core function is data science and analytics, the role increasingly involves using AI-assisted tools, identifying automation opportunities, building scalable data products, and improving how AI is used within the team.

What you'd actually do

  1. You’ll partner with product teams to help them identify important questions and answer those questions with data
  2. You’ll work closely with product managers, designers and engineers to develop key product success metrics, to set targets, to measure results and outcomes, and to size opportunities
  3. You’ll design, build and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables.
  4. You’ll partner closely with product researchers to build a holistic understanding of our customers, our products and our business.
  5. You’ll influence our product roadmap and product strategy through exploratory analysis and quantitative research

Skills

Required

  • 5 + years experience working with data to solve problems and drive evidence-based decisions
  • Strong SQL skills and solid grounding in statistics
  • Experience working closely with product teams
  • Proven track record of delivering actionable insights that drive measurable impact with minimal supervision
  • Strong product intuition, business acumen and ability to connect analysis to strategy
  • Excellent communication skills (technical and non-technical), with a focus on driving decisions and outcomes
  • Strong ownership, curiosity and growth mindset
  • Experience with a scientific computing language (e.g. Python)

Nice to have

  • Ability to effectively use AI tools (e.g. Claude Code, Cursor) to accelerate and improve your work
  • A mindset of automation and leverage - looking for ways to scale your impact beyond one-off analyses
  • Comfort working in ambiguous, fast-evolving environments where tools and workflows are rapidly changing
  • Experience with data modeling and ETL pipelines (esp dbt)
  • Experience building internal tools, data products or self-serve analytics capabilities
  • Experience leveraging AI across the data workflow - from ideation and coding to analysis and communication

What the JD emphasized

  • AI-assisted tools
  • AI-powered interfaces
  • AI within RAD