Data Scientist, Company Planning & Execution
Stockholm
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
Permanent — employment source
Employment type Permanent
Read the full posting
What you’ll work on
Full postingYou'll work closely with data scientists, engineers, PMs, and business partners across the company to help refine how Spotify executes at scale.
Build and maintain the data models, pipelines, and dashboards that provide visibility into how Spotify plans and executes.
From the employer’s posting
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
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.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience with a quantitative background in science, economics, engineering, or a related field.
- Proficient in SQL and Python, comfortable in BigQuery, and experienced with tools like dbt, Tableau, or Looker.
Preferred experience
- Experience with operational or work management data is a plus.
Qualification wording
5+ years of experience with a quantitative background in science, economics, engineering, or a related field.
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.
Tools in this posting
- Python
- SQL
- BigQuery
- dbt
- Tableau
- Looker
Source — Tool mentions in context
- 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.
Job description
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.
Employment type
Permanent
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Stockholm
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Sep 2, 2026
- Recorded sightings
- 17
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Aug 19, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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