wiz.io - Data Scientist Expert
Requirements
• 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. • 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. • 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. • Data scientist Expert
Responsibilities
• Lead applied research for AI-driven features in Wiz’s DSPM and Secret Detection domains • Conduct deep research and classification of sensitive data (PII, secrets) across complex structured and unstructured formats • Own the research lifecycle from raw data exploration and failure analysis to production-grade implementation • Identify and assess data security risks and use cases within cloud environments • Leverage LLMs to automate complex security research and enhance data classification at scale • Partner with Engineering, Security Research, and Product teams to define research goals and maintain production pipelines • Evaluate and optimize AI models and algorithms using real-world datasets to ensure high accuracy and scalability
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