Data Scientist - Audiobooks Analytics
The Data Scientist will use analysis, experimentation, forecasting, and statistical modeling to shape Spotify’s global audiobooks strategy across catalog, discovery, engagement, growth, and commercial initiatives. The role requires strong SQL and programming skills, business judgment, and cross-functional communication with senior stakeholders.
About the job
Responsibilities
- Develop data-driven strategies for audiobook catalog, content discovery, listener engagement, and subscriber growth.
- Evaluate product, content, licensing, and commercial opportunities using forecasting, scenario modeling, and impact measurement.
- Partner with Editorial, Personalization, Product, Finance, and Business teams to improve title selection, recommendation quality, and listener experience.
- Design and analyze A/B tests and quasi-experiments to measure product and go-to-market initiatives.
- Monitor audiobook business health, identify opportunities and risks, and translate findings into recommendations.
- Develop analytical datasets, tools, and reporting for repeatable insights.
- Improve data quality and scalable analytics practices with engineering and data partners.
- Present findings to senior leaders and influence product and business direction.
Requirements
- 3+ years of professional experience in data science or analytics.
- Fluency in SQL and proficiency in Python, R, or another programming language.
- Strong knowledge of statistical methods, experimentation, and causal inference.
- Strong business judgment and ability to communicate complex analysis clearly.
- Ability to structure ambiguous, open-ended problems and collaborate cross-functionally.
- Degree in Economics, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
Nice-to-haves
- Experience in consumer technology, media, subscriptions, marketplaces, product analytics, recommendation systems, content businesses, or digital marketplaces.
Skills
SQL, Python, R, Statistical Modeling, Experimentation, Causal Inference, A/B Testing, Forecasting, Scenario Modeling, Product Analytics, Recommendation Systems, Data Quality
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