Data Scientist Finance Data & Insights
@ Spotify

New York, NY
$121,898
On Site
Full Time
Posted 21 days ago

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XXXXXXXX XXXXXXXXXXX XXXXXXX***** @spotify.com
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Job Details

About the Data Scientist Finance Data & Insights Role at Spotify

We are looking for a Data Scientist to join our Royalties & Revenue team within the Finance Data & Insights organization. This role is perfect for someone who enjoys combining strong SQL and data skills with a deep curiosity for how financial data drives business decisions.

What You'll Do

  • Collaborate with cross-functional teams to enhance financial data systems.
  • Assist with legal and audit data pulls ensuring compliance and accuracy.
  • Provide accurate, timely outputs for internal Finance and Accounting teams.
  • Analyze large data sets related to royalties and subscription revenues.
  • Drive process efficiencies through automation and self-service reporting.

Who You Are

  • 2+ years experience in data analytics, financial data analysis preferred.
  • Strong SQL skills and hands-on experience with BigQuery and Google Sheets.
  • Experienced with visualization tools like Tableau or Looker Studio.
  • Adept at communicating technical and non-technical data insights.
  • Background in finance or related quantitative disciplines.
  • Familiarity with AI, Python, R, or similar programming languages is a plus.

Working Environment

This role is based in New York, NY, with a flexible work arrangement (in-office 2-3 days per week) aligned with EST working hours.

Key skills/competency

  • SQL
  • BigQuery
  • Data Analysis
  • Financial Data
  • Automation
  • Data Visualization
  • Python
  • R
  • Compliance
  • Cross-functional Collaboration
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How to Get Hired at Spotify

🎯 Tips for Getting Hired

  • Tailor your resume: Highlight SQL and data expertise.
  • Research Spotify: Understand their finance data ecosystem.
  • Customize application: Focus on financial data examples.
  • Prepare for interviews: Emphasize cross-functional experiences.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries on sample datasets.
Review BigQuery functions and optimization techniques.
Work on automating data pipelines using Python.
Explore data visualization tools like Tableau.

Behavioral Questions

Describe a challenge solved with data.
Explain cross-functional teamwork experience.
Detail handling multiple project deadlines.
Discuss adapting to feedback in projects.

Frequently Asked Questions