Data Scientist & ML/AI Engineer

We are looking for a Data Scientist & ML/AI Engineer to join a high-tech company based in Ra’anana!
This is a temporary position with possible extension.

We are looking for a highly skilled Data Scientist & ML/AI Engineer hands-on leaders to join our eSIM team for a project focused on building advanced AI models for fraud detection and anomaly spotting. The ideal candidate will have strong expertise in data science, machine learning, and AI engineering, with a proven track record of delivering production-ready solutions. We highlight that most used data will be unlabelled logs; the role requires to be familiar with unsupervised learning techniques in adition to semi-supervised and supervised approaches.
The project consist of developing a fraud and anomaly detection module by leveraging logs and information collected by our existing platform. The goal is to design, implement, and optimize algorithms and machine learning models to detect anomalies in eSIM related transactions (e.g. profile downloads).
You are expected to lead the AI project through the complete lifecycle including defining problems, designing sol

דרישות:

Education: Master’s or Ph.D. in Computer Science, Data Science, AI, or related field.
Experience: Minimum 4 years in machine learning and AI engineering, with hands-on experience in fraud detection or anomaly detection.
Product Domain Skills:
Real-Time Detection: Experience designing models for real-time anomaly detection in high-throughput environments.
Transaction & Log Analysis: Expertise in analyzing large volumes of transactional logs and network events to identify anomalies and suspicious behaviors.
Telecom & eSIM Ecosystem: Understanding of eSIM lifecycle management, including profile downloads, activation, and provisioning processes.
Fraud Patterns in Telecom: Familiarity with fraud scenarios such as SIM swap, identity theft, and unauthorized profile downloads in mobile networks.
Technical Skills:
Programming: Python (mandatory), Database querying.
Frameworks & Libraries: TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, Python Outlier Detection library.
Data Engineering: ETL pipelines, data preprocessing, feature engineering.
Cloud Platform: Azure ML, Fabric, Azure ecosystem.