Data Scientist - Digital Interactive Entertainment Platform

Responsibilities :

- Experience from e-commerce, online payments, fraud/risk management, social networking, or gaming industry

- Master's degree required in a quantitative discipline such as Computer Science, Mathematics, Statistics, Economics, Engineering, Operations Research; PhD preferred

- Analyze large data sets to identify behavior trends among good users and bad actors, using statistics, data mining, and machine learning techniques.

- Develop algorithms and heuristics that will quickly identify fraudulent transactions, fraudulent account creation, account compromise and other high-risk activities

- Research new predictive modeling techniques, assist in business case development for investing in new data technologies needed to support best-of-breed fraud detection

- Build prototype tools for investigating fraud events/behavior and analyzing system-wide trends

- Rapidly respond to operational needs by providing adhoc analytical support

- Partner with Engineering and Operations teams to define product requirements

- Build automated reports (e.g. Tableau), dashboards, and performance metrics, as requested

Job Requirements :

- Ability to thrive in a dynamic, fast-paced environment with ability to multi-task.

- Strong problem solving and team collaboration attitude.

- Results-driven and highly quantitative.

- True passion for understanding customer behavior on-platform and in-game.

- Strong interpersonal and communication skills.

- Strong analytical skills including the ability to interpret and manipulate large structured and semi-structured data, develop recommendations and analysis.

- Experience to manage and implement advanced analytics projects which solve complex analytical problems using machine learning, pattern recognition, and/or data mining technologies.

- Be familiar with coding in Python/Java/SCALA, and SQL/NoSQL, tools (e.g. R) and Apache Spark framework.

- Ability to communicate insights to technical and non-technical audiences.

- Self-motivated, work well both independently and as part of an agile team.