Analyze Spotify’s planning and execution data to develop hypotheses, statistical and machine learning models, data pipelines, dashboards, and actionable recommendations. The role translates complex operational and strategic information into narratives, reports, and decision frameworks for leaders. It also explores AI and automation for faster insight generation and collaborates with data scientists, engineers, product managers, and business partners across the company.
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.
Spotify London, England Office
London, United Kingdom
Similar Jobs
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.
Top Skills:
LanggraphLlm ApisMlopsPydantic Ai
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads the vision, strategy, and execution of AI-powered data and analytics capabilities for Medical Affairs. Oversees patient journey analytics, advanced segmentation, stakeholder evaluation, data architecture, governance, and AI automation frameworks. Evaluates external innovations, builds proprietary solutions, manages analytics delivery teams, and advises senior leadership on data investments, innovation roadmaps, compliance, ethics, and competitive advantage.
Top Skills:
Advanced SegmentationAi/MlAutomation FrameworksData ArchitectureData GovernanceData ScienceHcp Network AnalysisHealthcare Data PlatformsPatient Journey Analytics
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Owns the global operational backbone of the InsightXplorer medical insights platform, including access provisioning, licensing, user administration, request intake and triage, hosting coordination, governance, reporting, metrics, workload visibility, and resource oversight. The role manages competing priorities across regions, coordinates recurring team cadences, supports leadership-ready reporting, and oversees contracted resources while collaborating with technical partners and cross-functional stakeholders.
Top Skills:
Access GovernanceAnalytics PlatformsData Platform OperationsInsightxplorer
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
