Investigate evolving fraud trends and consumption habits to enhance detection capabilities.
Apply your expertise in quantitative analysis, data mining, and data presentation to help automate, optimize and understand key business problems and solutions.
Build data and tooling to empower operational and exploratory data analysis while optimizing for speed, accuracy, and quality.
Work closely with cross-functional teams of data and backend engineers, and product managers.
Partner with a broad range of stakeholders across music, podcasts and audiobooks to consistently uphold platform integrity.

A Bachelor's degree in Data Science, CS, or another quantitative field.
1+ years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines.
Deep understanding of data with expertise in data manipulation and design (SQL) and experience in Python.
Strong analytical skills, with the ability to turn data into actionable insights and recommendations.
Strong problem-solving skills, intellectual curiosity, and a proactive approach to identifying new opportunities for fraud detection.
A continuous learner, excited by new technologies and able to pick up new tools and frameworks quickly.

Associate Data Scientist – User Fraud

Key skills