Temporary position for three months.

We are looking for a skilled Data Scientist to develop a fraud and anomaly detection module by

leveraging logs and information collected by our existing platform, combined with mobile

operator data. The goal is to design, implement, and optimize algorithms and machine learning

models to detect anomalies in eSIM profile downloads.

What will your task look like?

- Collect, analyze and interpret data sets from various sources, including Amdocs eSIM platform

logs and mobile operator data.

- Synthetic data generation to train and challenge the model

- Perform data analysis and preprocessing to uncover patterns and improve detection accuracy.

- Choose algorithms, develop machine learning models to identify and prevent fraudulent

activities.

- Monitor and improve the performance of models.

- Collaborate with with cross-functional teams.

- Document the development and design decisions.

Areas of expertise needed

- Master's degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a

related field. A PhD is a plus..

- Minimum of 4 years of experience in data science; experience in anomaly detection is highly

appreciated.

- Proven experience with machine learning frameworks such as Python, NumPy, TensorFlow, or

PyTorch.

- Proficiency in using Azure AI and other relevant tools and technologies.

- Excellent analytical and problem-solving abilities.

- Ability to work collaboratively in a team environment, ability to communicate complex

technical concepts eMectively.