Data Scientist
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Requirements
• You have a degree in Computer Science, Statistics, Economics, Operations Research, quantitative social science, or a related field (or equivalent experience) • You bring 4+ years of experience as a Data Scientist influencing product decisions through data • You’re highly proficient in SQL and Python and comfortable working with large-scale datasets • You use AI-powered tools (e.g., Cursor, Copilot) to accelerate analysis and workflows • You have strong product intuition and a results-focused perspective— you seek the “why” behind the data • You have experience with A/B testing, causal inference and advanced statistical methods, and exercise strong judgment in methodological choices • You understand machine learning systems and can evaluate models beyond offline metrics, applying human judgment to quality and impact • You thrive in ambiguous, zero-to-one environments and enjoy defining metrics & opportunities for entirely new product categories • You’re motivated by creating real value for music fans and music creators • Where You'll Be • We offer you the flexibility to work where you work best! For this role, you can be within the EST timezone region as long as we have a work location. • This team operates within the Eastern Standard time zone for collaboration • The United States base range for this position is $110,018 - $157,169 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future. • 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.
Responsibilities
• Own analytical projects end-to-end, from hypothesis generation and data exploration to recommendations for product leadership • Develop and own success metrics for generative music features and systems • Design and analyze A/B tests and causal studies to evaluate product and model impact • Perform exploratory analyses to uncover opportunities that improve experiences for listeners and artists • Build scalable dashboards to monitor feature health and ecosystem impact • Design and run evaluations for generative music systems, assessing risks and opportunities across prompts, outputs, and quality • Collaborate with Product, Design, Research, Marketing, and Engineering to translate insights into product requirements • Partner closely with Engineers and AI Researchers to integrate evaluation signals into model development workflows • Communicate complex findings through clear, actionable narratives that inform product strategy and roadmap decisions