Fraud Analyst

Description

Play Perfect is a fast-growing mobile gaming company that provides entertainment to millions of users around the world. The company is headquartered in Tel Aviv.

With a team of talented and passionate developers, designers, industry experts and gamers, Play Perfect is at the forefront of creating immersive gaming experiences that engage players on a whole new level.

As we continue to push the boundaries of what is possible in gaming, Play Perfect is poised to shape the future of the industry and redefine what it means to be a skill-based gaming company.

As we expand, we're looking for a rockstar Fraud Analyst to join our great team.

Responsibilities

• Analyse customer behaviour and identifying suspicious trends and suggesting possible solutions, estimating impact
• Research complex fraud patterns, adversarial behaviors, and emerging threats
• Develop and maintain the fraud models, including implementing new methodological
• Analyze large-scale datasets to identify emerging fraud trends, patterns, and techniques.
• Generate actionable insights that improve decision accuracy and guide business stakeholders on model usage, impact, and implementation.
• Collaborate with internal colleagues across departments, including Product Managers, Data Scientists and Data Engineers.
  
  

• At least 3 years of professional work experience as a Fraud Analyst or as a Business Analyst
• Self-reliant, proactive, and capable of taking initiative, with the ability to work independently while driving projects forward with minimal supervision
• High proficiency in SQL and experience in querying large and complex data sets
• Knowledge of the payment ecosystem and risk fields and gaming - a big advantage
• Self-reliant, proactive, and capable of taking initiative, with the ability to work independently while driving projects forward with minimal supervision
• Manage multiple tasks at a time in a fast-paced environment
• Exceptional ability to understand data and to transform it into insights
• BA/BSc in Statistics / Industrial Engineering or other quantitative fields