Data Scientist, Company Planning & Execution

How does a company with thousands of people building hundreds of products stay focused on what matters most? That's the question the Company Planning and Execution (CPE) team works on every day. We design the systems, processes, and insights that help Spotify plan, prioritise, and deliver at scale.

As a Data Scientist on CPE, you'll sit at the intersection of data, strategy, and operations. You'll bring clarity to complex questions by turning operational and strategic information into clear stories, recommendations, and decision frameworks that help leaders and teams act faster and smarter. You'll also explore how AI and automation can change the way people access insights and make decisions.

You'll work closely with data scientists, engineers, PMs, and business partners across the company to help refine how Spotify executes at scale. If you like making sense of ambiguity, care about how organisations work, and want your analysis to shape real decisions, this is the role.

• Formulate hypotheses related to how Spotify plans and delivers, and communicate insights effectively to a range of audiences.
• Apply analytical techniques — including statistical models and machine learning — to identify trends and generate insights that improve how we work.
• Build and maintain the data models, pipelines, and dashboards that provide visibility into how Spotify plans and executes.
• Develop structured narratives and recommendations — not just charts, but the "why" and "so what" — in our semi-annual Planning and Execution Insight reports and recurring briefings.
• Explore how AI and automation can make insights faster to produce and easier to access across the company.

• Curious about how organisations work — not just the data, but the decisions and systems behind it.
• 5+ years of experience with a quantitative background in science, economics, engineering, or a related field.
• Strong interpersonal skills and comfortable working with multiple stakeholders across levels and functions.
• Able to take messy, complex datasets and turn them into clear recommendations and stories that land with non-technical audiences.
• Proficient in SQL and Python, comfortable in BigQuery, and experienced with tools like dbt, Tableau, or Looker.
• Experience with operational or work management data is a plus.

• This role is based in London or Stockholm.
• We offer you the flexibility to work where you work best, with 2–3 days per week in the office.