Minimum Qualifications

• 5+ years of experience in applied Data Science and AI engineering 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).
• Hands-on experience building Autonomous Agent architectures (e.g., LangGraph, multi-agent workflows, tool-calling, and state machines) and implementing rigorous evaluation frameworks (Evals, LLM-as-a-judge, benchmark suites).
• 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) with the ability to deliver production-ready code.
• An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience.

Preferred Qualifications

• Experience in cybersecurity (cloud security, threat detection, investigation, or network telemetry).
• 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.
• 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 an Applied 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.