Data Scientist

Come join the organization that is redefining security for the AI era. As one of the fastest-growing startups ever, we enable teams to secure cloud and AI applications by connecting code, cloud, and runtime into a single shared context. Trusted by security teams all over the world, we have a proven track record of success and a culture that values world-class talent. Not to mention, we're now powered by Google, meaning we offer our customers an AI-powered platform that harnesses Google’s Threat Intelligence and Security Operations to better detect, prevent, and respond to threats across all environments, allowing for further innovation.

Our Wizards from all over the globe work together to protect the infrastructure of our customers, including over 65% of the Fortune 100, who trust us to scan and secure over 230 billion files daily. We’re honored to be a leading player in a massive and growing market, and we continue to look for exceptional Wizards who are eager to make a significant impact on our team. At Wiz, you’ll have the freedom to think creatively, dream big, and use your full range of skills to contribute to our momentous growth. Come join our team and help us create secure cloud environments that allow even the best companies to move faster, all while having some fun!

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.