Minimum qualifications

• 5+ years of experience in leading data science and machine learning projects, with significant hands-on work building LLM-based applications or AI agents.
• Deep practical experience with LLMs (prompt engineering, fine-tuning, model selection, and understanding trade-offs across providers and model families).
• Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch).
• An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience.

Preferred qualifications

• Experience with distributed cloud systems and hands-on familiarity with cloud-native architectures at scale.
• Strong knowledge of deep learning models and common model architecture such as transformer models.
• Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.
• Excellent communication (both written and verbal) and presentation skills.
• Ability to work independently in a fast-paced environment and come up with creative solutions to challenging problems.

About the job

We’re looking for a Data scientist Expert to join us and spread the power of Wiz. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at Wiz. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the company’s security posture.

Responsibilities

• Lead applied research on AI agents and LLM-driven features in the Wiz platform - from autonomous threat investigation agents to AI-powered security operations workflows.|Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security.
• Collaborate with engineering teams to design, build, and maintain production pipelines.
• Work closely with the Security Research and Product teams to define research goals.
• Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
• Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.