Data Scientist - Company Planning and Execution (CPE)
Spotify
Data Scientist - Company Planning and Execution (CPE)
Job Description
Join our Company Planning and Execution (CPE) team at Spotify and help shape how we turn strategy into action across the company. The CPE team’s mission is to continuously improve how we develop Spotify as a product and a business to unlock the company strategy. We design and evolve the systems, processes, and insights that help Spotify plan, and execute at scale, ensuring every team can focus on delivering value to millions of users around the world.
As a Data Scientist, you will work at the intersection of data, strategy, and operations. You will use analytical techniques to uncover insights that guide how Spotify plans, prioritizes, and drives execution. You will also explore ways to integrate AI and automation into our workflows and operating model to support smarter and more efficient ways of working.
With access to Spotify’s extensive data ecosystem, you will transform complex information into clear, actionable insights that inform decision-making across teams. Your curiosity and analytical skills will help identify opportunities for improvement and shape how we measure progress and impact.
You will collaborate with analysts, data scientists, engineers, and business partners across Spotify. Continuous learning and experimentation are part of our culture. This role offers the opportunity to grow your craft, contribute to meaningful strategic work, and help refine how Spotify executes at scale.
Locations
- London, United Kingdom
- Stockholm, Sweden
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
75,000 - 120,000 GBP / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- SQLintermediate
- Pythonintermediate
- BigQueryintermediate
- dbtintermediate
- Tableauintermediate
- Lookerintermediate
- statistical modelsintermediate
- machine learningintermediate
Required Qualifications
- You have experience analyzing large datasets and translating them into actionable insights (experience)
- You are curious and creative, with a focus on accuracy and clarity in your work (experience)
- You have experience turning large, complex datasets into clear insights, recommendations, and stories (experience)
- You enjoy working with technical and business teams to turn data into impact (experience)
- You are comfortable working in a cloud-based data environment such as BigQuery and using modern data tooling like dbt (experience)
- You are proficient in SQL and Python, and have experience building dashboards with tools like Tableau or Looker (experience)
- You have a quantitative background in Computer Science, Statistics, Engineering, or a related field (experience)
Preferred Qualifications
- Experience with operational or work management data is a plus (experience)
Responsibilities
- Collaborate with data scientists, analysts, engineers, and business teams to deliver analysis and insights that improve how Spotify executes its strategy
- Build and maintain reliable data models, pipelines, and dashboards that bring together information from across Spotify’s ecosystem
- Create scalable and interactive reports and visualizations that turn data into clear insights and actionable recommendations
- Translate business questions and user needs into analytical approaches that uncover opportunities, inform priorities, and guide decision-making
- Apply analytical techniques, including statistical models and machine learning, to identify trends and generate insights that improve how we work
- Integrate AI and automation into data workflows and planning tools to make processes more efficient and intelligent
- Contribute to improving our data foundations, documentation, and analytical best practices within the CPE team
- Develop structured narratives and recommendations that help teams understand the “why” behind the data and guide their next steps
Benefits
- general: 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
Tags & Categories
Data Scientist - Company Planning and Execution (CPE)
Spotify
Data Scientist - Company Planning and Execution (CPE)
Job Description
Join our Company Planning and Execution (CPE) team at Spotify and help shape how we turn strategy into action across the company. The CPE team’s mission is to continuously improve how we develop Spotify as a product and a business to unlock the company strategy. We design and evolve the systems, processes, and insights that help Spotify plan, and execute at scale, ensuring every team can focus on delivering value to millions of users around the world.
As a Data Scientist, you will work at the intersection of data, strategy, and operations. You will use analytical techniques to uncover insights that guide how Spotify plans, prioritizes, and drives execution. You will also explore ways to integrate AI and automation into our workflows and operating model to support smarter and more efficient ways of working.
With access to Spotify’s extensive data ecosystem, you will transform complex information into clear, actionable insights that inform decision-making across teams. Your curiosity and analytical skills will help identify opportunities for improvement and shape how we measure progress and impact.
You will collaborate with analysts, data scientists, engineers, and business partners across Spotify. Continuous learning and experimentation are part of our culture. This role offers the opportunity to grow your craft, contribute to meaningful strategic work, and help refine how Spotify executes at scale.
Locations
- London, United Kingdom
- Stockholm, Sweden
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
75,000 - 120,000 GBP / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- SQLintermediate
- Pythonintermediate
- BigQueryintermediate
- dbtintermediate
- Tableauintermediate
- Lookerintermediate
- statistical modelsintermediate
- machine learningintermediate
Required Qualifications
- You have experience analyzing large datasets and translating them into actionable insights (experience)
- You are curious and creative, with a focus on accuracy and clarity in your work (experience)
- You have experience turning large, complex datasets into clear insights, recommendations, and stories (experience)
- You enjoy working with technical and business teams to turn data into impact (experience)
- You are comfortable working in a cloud-based data environment such as BigQuery and using modern data tooling like dbt (experience)
- You are proficient in SQL and Python, and have experience building dashboards with tools like Tableau or Looker (experience)
- You have a quantitative background in Computer Science, Statistics, Engineering, or a related field (experience)
Preferred Qualifications
- Experience with operational or work management data is a plus (experience)
Responsibilities
- Collaborate with data scientists, analysts, engineers, and business teams to deliver analysis and insights that improve how Spotify executes its strategy
- Build and maintain reliable data models, pipelines, and dashboards that bring together information from across Spotify’s ecosystem
- Create scalable and interactive reports and visualizations that turn data into clear insights and actionable recommendations
- Translate business questions and user needs into analytical approaches that uncover opportunities, inform priorities, and guide decision-making
- Apply analytical techniques, including statistical models and machine learning, to identify trends and generate insights that improve how we work
- Integrate AI and automation into data workflows and planning tools to make processes more efficient and intelligent
- Contribute to improving our data foundations, documentation, and analytical best practices within the CPE team
- Develop structured narratives and recommendations that help teams understand the “why” behind the data and guide their next steps
Benefits
- general: 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
Tags & Categories