Data Analyst- Fraud Detection at AppsFlyer

Herzliya, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

30 May, 26

Salary

0.0

Posted On

02 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Looker, BigQuery, AWS Services, Airflow, Data Analysis, Fraud Detection, Machine Learning, Deep Learning, AI Techniques, Data Exploration, Algorithm Analysis, Pandas, Numpy, BI Tools

Industry

technology;Information and Internet

Description

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. What you have: 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. Bonus Points: 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. As a global company operating from 25 offices across 19 countries, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners. “As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO

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Responsibilities

The Data Analyst will analyze large, complex datasets to identify fraud patterns and emerging threats, while also supporting the development, evaluation, and monitoring of fraud-detection models. Key tasks include writing high-performance SQL queries, using Python for analysis, and building analytical tools and dashboards.