spotify - Data Scientist - User Fraud
Requirements
• At least two years of experience working with large, complex datasets using Python, SQL or R. • Experience in creating data visualizations using tools like matplotlib, ggplot, Looker Studio, etc. • Degree in a quantitative field such as data science, computer science, statistics, economics, mathematics. • Strong understanding of working with data pipelines and anomaly detection methods. • Solid experience with statistical modeling and machine learning techniques.
Responsibilities
• Analyze user and system data to detect and assess risks of artificial or fraudulent activity on Spotify. • Build data science and machine learning solutions for fraud prevention analysis. • Communicate insights and recommendations using clear visuals and storytelling techniques. • Develop scalable data pipelines and dashboards to monitor performance and support decision-making processes.
Benefits
• Join an exciting mission to protect Spotify from unwanted behavior by detecting and preventing fraudulent activities across all business areas. • Work with a cross-functional team of data scientists and machine learning engineers on continuous experimentation, iteration, and delivery of new solutions for user fraud detection and prevention. • Contribute to the development of scalable data pipelines and dashboards that support decision-making processes within Spotify's User Fraud R&D Studio.
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