Experienced Data Scientist

At Thales, we know technology has the ability to make our world more secure, sustainable, and inclusive – and that it’s all driven by human intelligence.

Because it takes human intelligence to build and power the systems and solutions that people depend on every day. So we stay curious and make space for diverse points of view. We share what we know and we challenge what’s possible.

We’re driving progress in some of the world’s most important industries - from the bottom of the oceans to the depths of space and cyberspace - and from manufacturing to engineering, we work together to build a future we can all trust.

Imperva, a Thales company, is a globally recognized cybersecurity leader, dedicated to securing data and applications across diverse environments. Our cutting-edge solutions empower organizations to safeguard their most critical assets, ensuring robust protection against emerging threats.

We’re proud to be recognized as one of Israel’s Top 50 High-Tech Companies to Work For in 2024 (Dun & Bradstreet) and offer a flexible hybrid work model from our Tel Aviv office.

We are looking for a highly technical and innovative, hands-on Experienced Data Scientist to join our Threat Research group.

Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for new products, and drive innovation and thought leadership in cybersecurity.

Key Responsibilities:

• Lead and execute data-driven research projects in application and data security, using advanced machine learning and deep learning techniques.
• Own the end-to-end research process: from ideation and prototyping to delivering models to production environments.
• Develop, implement, and optimize innovative security solutions to be integrated into Imperva’s products.
• Analyze large-scale security data (network traffic, application requests, database transactions) to uncover hidden patterns, threats, and attack vectors.
• Contribute to team knowledge sharing and thought leadership (e.g., technical blogs, patents, conference presentations, workshops).
  
  

• 4+ years of hands-on experience researching, developing, and delivering machine learning models in high-scale, production environments (Python preferred).
• Strong background in analyzing large, complex datasets using SQL, Spark, or similar tools.
• Deep experience with analytics, machine learning, and deep learning frameworks: Scikit-learn, SciPy, TensorFlow, Pandas, NumPy, PyTorch, Keras.
• Demonstrated ability to solve multidisciplinary, data-driven problems.
• Excellent teamwork and communication skills.
• Experience in application or data security (strong advantage).
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Experience with Kubernetes (K8s) and microservices infrastructure is a plus.
• Experience with CI/CD practices and the full lifecycle of ML model development, from data preparation to deployment and monitoring, is a strong advantage.
• Ph.D. or M.Sc. in Computer Science, Engineering, Math, or another quantitative/technical field is valued, but not required if you have strong relevant professional experience.
• Strong English and presentation skills are an advantage.