• Bachelor's degree in Computer Science, Engineering, or a related technical/quantitative field, or equivalent practical experience in risk, abuse, fraud, and/or data protection
• 3 years of experience in risk analysis, anti-abuse, fraud investigations/detection/prevention, data science, and/or data analysis
• Experience querying (e.g., SQL), building data pipelines/dashboards, and analyzing datasets
• Experience with machine learning (e.g., regression, classification, clustering) on large datasets
• Experience collecting, managing, and synthesizing large data sets and information from disparate sources, statistical modeling, data mining, and data analysis
• Domain knowledge or interest in security, malware, phishing or related topics
• Understanding of fraud dynamics in the online world and sense of mission in protecting users