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Spotify

Data Scientist - Business Analytics

London, England, United Kingdom

Location
London, England, United Kingdom
Work
On-site
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
Not stated
Posted
2 weeks ago

About the role

We are looking for a Data Scientist to join the Business Analytics team within Spotify’s Business Strategy and Insights organization. Our team tackles some of Spotify’s most consequential strategic questions, shaping the trajectory of our business and improving the experiences of our over 700M active users across more than 180 countries.

In this role, you will use data analysis, experimentation, and statistical modeling to identify, assess, and launch a broad range of new initiatives and product features focused on payments and payments fraud. You will also regularly assess the health of our business and identify areas of opportunity, translating these insights into clear, actionable recommendations for senior leadership.

At Spotify, you'll have access to some of the richest datasets in the world and the autonomy to explore them creatively and rigorously. Above all, your work will shape how the world listens, discovers, and connects through audio.

What You'll Do

  • Develop data-driven strategies to support the growth of Spotify’s active users and subscribers
  • Create and communicate impactful findings and recommendations that improve the
  • Premium product and the way we process payments
  • Model and forecast the impact of new business initiatives
  • Work closely with business partners to understand the changes they are driving and help them discover new opportunities for growth
  • Analyze experiments (A/B tests; quasi-experiments) to measure the impact of new features and go-to-market initiatives
  • Present your findings to senior leaders, influencing the course of our business

Who You Are

  • You have 5+ years of professional experience in data science or analytics, ideally at a consumer tech company or top-tier consulting firm.
  • You are fluent in SQL and Python or R, and have a strong grasp of statistical methods and causal inference. Direct experience with product analytics, experimentation, or payments is a plus.
  • You enjoy partnering with a range of cross-functional stakeholders and working on varied projects involving different products and problem spaces.
  • You have a strategic mindset and an eye for cleanly extracting the “so what” from complex, technical analyses.
  • You are an excellent communicator adept at presenting to senior leadership and audiences of varying levels of technical knowledge.
  • You are comfortable working through ambiguous, complex problems and don’t get discouraged when the path forward isn’t immediately clear.
  • You hold at least a Bachelor’s degree in Economics, Mathematics, Statistics, Computer Science, or a related quantitative field.

Where You'll Be

  • This role is based in London
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

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.

Source

Posted by Spotify on their own hiring page, jobs.lever.co. OptiTalent shows it as published, read 07 Nov 2026 00:24 UTC; the original is the reference.

View the original ad ↗

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