• 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.
• Master's degree in Statistics, Applied Mathematics, Computer Science, Engineering, Data Science, Analytics, or related fields.
• 6 years of experience in coding (e.g., Python, Java), databases, and/or querying (e.g., SQL and MySQL).
• Experience in complex engineering systems and processes. 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.