Role

• Expertise in quantitative analysis, data mining, and the presentation of data to understand fraud, and how to prevent it.
• Build, maintain, and tune advanced predictive models to understand the impact of specific fraudulent behaviors, trends and patterns.
• Work closely with cross-functional teams of data and backend engineers, analysts, user researchers, product managers
• Build and analyze dashboards, reports and key datasets to empower operational and exploratory analysis of fraud.
• Offline analysis of customer data to tune rules, exposes patterns, research anomalies, reduce false positives, and build executive and project-level report
• Communicate data-informed insights and recommendations to key stakeholders, engineering and product partners.

Qualifications

• At least 5 years of knowledge and experience with regard to fraud case management, predictive modeling and analysis, predictive software development
• An MS/PhD in CS, Machine Learning, Operational research, Statistics or in a highly quantitative field. PhD strongly preferred.
• Knowledge of cybercrime – account takeover, Card not Present (CNP) fraud, promotion abuse, social engineering etc.
• Previous experience working in fraud detection and prevention, with an understanding of the impact that has on other areas in the company where business and product decisions are made.
• Coding skills for analytics and data manipulation (SQL, R, Python, SAS), practical understanding of SQL and NoSQL databases
• Knowledge of machine learning algorithms including classifiers, clustering algorithms, and anomaly detection a plus
• Strong analytical and statistical analysis skills in order to extract insights and recommendations
• Strong communication and data presentation skills
• Fluent in English with strong communication skills (both written and verbal)

上班地址：徐汇区桂箐路65号新研大厦B座24楼