Data Scientist, Company Planning & Execution

Company: Spotify
Location: Stockholm
Type: hybrid
Posted: Sep 2, 2026
Views: 2

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.

What You'll Do

  • 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.

    • Who You Are

  • 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.

    • Where You'll Be

  • 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.
    • Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
    At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
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    About the Company

    Name: Spotify
    Website: https://4dayweek.io

    4dayweek.io is a job board dedicated to helping professionals find jobs with a 4-day work week and other flexible schedules. It lists thousands of roles at companies committed to better work-life balance, including 4-day weeks, 9-day fortnights, flexible hours, and more. The platform verifies each company's schedule policy and offers features like job alerts, auto-apply, and a database of companies with reduced-hours policies.

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