Data Analyst- Fraud Detection

AppsFlyer is the #1 market leader in mobile app measurement & mobile attribution platforms. We run at a massive scale - for a SaaS and big data company - processing more than 100 billion events daily.

Fueled by the AppsFlyer platform, Protect360 is the leading anti-fraud solution in the market, protecting advertisers from fraudulent traffic and saving millions of dollars for our customers.

We detect fraudulent traffic in real time using machine learning, deep learning, and advanced AI techniques applied on massive data streams.

We’re looking for a Data Analyst to join the Protect360 algorithms team and play a key role in researching fraud patterns, analyzing large-scale data, and supporting the development and monitoring of fraud-detection algorithms.

This role is highly R&D-oriented, with deep involvement in data exploration, algorithm analysis, and close collaboration with data scientists, engineers, and product partners.

A partial list of our tech stack includes: SQL, Python, Looker, BigQuery, AWS services, Airflow, and more.

What You'll Do

• Analyze large, complex datasets to identify fraud patterns and emerging threats.
• Design and write high-performance SQL queries for large-scale data analysis.
• Use Python for data analysis, exploration, validation, and workflow automation.
• Support the development, evaluation, and monitoring of fraud-detection models.
• Build analytical tools, reports, and dashboards to track algorithm performance and fraud trends.
• Collaborate with data scientists, engineers, and product managers on R&D initiatives.
• Translate business and product questions into data-driven insights and recommendations.
  
  

• 3+ years of experience as a Data Analyst in a large-scale data or R&D environment.
• B.Sc. in Industrial Engineering, Statistics, Mathematics, Computer Science, or a related field.
• Strong proficiency in SQL and experience working with large-scale datasets.
• Hands-on experience with Python for data analysis (e.g., pandas, numpy).
• Hands-on experience with BI tools such as Looker, Power BI, Tableau, or similar.
• Strong analytical skills and ability to solve complex, ambiguous problems.
• Clear communicator with both technical and non-technical stakeholders.
• Independent, proactive, and comfortable in a fast-paced environment.
  
  

• Experience in ad-tech, mobile marketing, or fraud detection.
• Experience working closely with data science or algorithm teams.
• Familiarity with machine learning or data science workflows.
• Volunteering or social impact involvement.
• Being referred by an AppsFlyer team member.