Data Scientist – Discovery Mode

Spotify

Data Scientist responsible for analytics and model evaluation in Discovery Mode at Spotify. Collaborating with ML engineers and product managers to enhance promotional tools for music creators.

Posted 6/22/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

BigQueryPythonSQL

About the role

Key responsibilities & impact

Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization
Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact
Design and execute rigorous experiments to evaluate model quality, measure outcomes, and guide model development
Conduct deep-dive analyses to assess model performance and translate findings into clear, actionable recommendations for product and business stakeholders
Build, maintain, and evolve dashboards that track model health, customer metrics, and program performance
Collaborate with product managers, engineers, and cross-functional partners to align analytical priorities with squad goals and customer needs
Contribute to the broader Product Insights community by sharing best practices and helping raise the bar for analytics across Discovery Mode

Requirements

What you’ll need

4+ years of experience in a data science role and a degree in data science, statistics, economics, mathematics, or a related quantitative field
Experience measuring customer outcomes, defining KPIs, and connecting analytical insights to product decisions
Design and implement A/B tests, understand when experimentation is the right tool, and interpret results with appropriate rigor
Experience evaluating machine learning model performance and partnering with ML engineers to improve model and customer outcomes
Comfortable working in a highly technical environment and collaborating closely with engineering partners
Communicate complex statistical concepts clearly to both technical and non-technical audiences
Strong data science fundamentals, including Python, SQL, BigQuery, dbt, data storytelling, and experience working within cross-functional product teams
Experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale

Benefits

Comp & perks

Flexibility to work where you work best within the EST timezone region

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningA/B testingstatistical analysisdata storytellingmodel evaluationKPI definitionexperiment designPythonSQL

Soft Skills

communicationcollaborationanalytical thinkingproblem-solvingstakeholder engagement