At a glance
- Experience
- 5+ years experience
- Location
- Herzliya
About the role
- AppsFlyer is looking for a data scientist to join the team and further improve fraud detection capabilities.
- This position involves analyzing evolving fraud patterns, developing and deploying advanced prevention components, and leveraging domain expertise, data tools, and modern AI methods to stay ahead of emerging threats.
Responsibilities
- Mine massive data sets to uncover fraud patterns and prevention opportunities.
- Develop and productionize large-scale ML, DL, and AI models to detect and prevent fraudulent activity.
- Translate business and product needs into scientific, explainable, and high-impact solutions.
- Design and maintain end-to-end ML pipelines - from data ingestion and feature engineering to serving and monitoring in production.
- Collaborate closely with product, engineering, and business teams to drive data-driven decisions.
- Stay current with AI and ML research and evaluate new technologies to strengthen Protect360’s algorithms.
Requirements
- M.Sc in Computer Science, Mathematics, Statistics, Engineering or a related field
- 5+ years of experience in applied Data Science or Algorithmic Development, preferably in large-scale production environments.
- Hands-on experience in training and fine-tuning machine learning, deep learning, and AI models
- Strong programming skills in Python and proficiency in SQL.
- Solid understanding of data pipelines, MLOps practices, and working with huge datasets.
- Ability to mentor, collaborate, and communicate complex ideas clearly to diverse audiences.
- A fast learner, problem solver, and end-to-end owner with a strong “can-do” approach.
Preferred qualifications
- Experience in the ad-tech industry or with fraud detection systems.
- Familiarity with LLMs, generative AI, or representation learning for anomaly detection.
- Proven track record working with large-scale distributed data systems.
- Being introduced by an AppsFlyer employee
Skills
- Python
- Spark
- TensorFlow
- PyTorch
- Kafka
- AWS Services
- Airflow
- Scala
- BigQuery
- SQL
