Data Scientist

• Own AI product creation end-to-end - from the initial concept through building prototypes to full-scale production.
• Drive innovation by developing and integrating ML and Generative AI solutions into Cynet's core cybersecurity products: Endpoint, XDR, Network Detection, and Posture Management.
• Analyze massive volumes of security data to uncover hidden patterns, threats, and insights.
• Develop and fine-tune models with state-of-the-art optimization strategies and performance metrics.
• Contribute to and expand our AI infrastructure, including data pipelines, evaluation tools, and deployment frameworks.
• Conduct rigorous experimentation, explain and monitor the real-world performance of your models.
• Write production-ready code that makes it into our deployed AI systems.

• 3+ years of experience in researching, developing and delivering ML solutions in production-scale environments.
• Solid foundation knowledge of data science, machine learning, and statistics.
• Demonstrated analytical thinking and a deep understanding of data - its structure, context, and the insights it can unlock.
• Strong Python programming skills with fluency in AI/ML frameworks: Scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain, etc.
• Expertise in working with large-scale datasets using SQL, Spark, or similar tools.
• Proven success translating product or business needs into working AI systems.
• Fast learner, creative, and comfortable working in a dynamic startup environment.
• Good communication skills, able to explain complex ideas and findings to both technical and business audiences.

• Experience with cybersecurity-related data or product domains.
• Hands-on knowledge in working with LLMs and building AI agents.
• Familiarity with AWS cloud environment and MLOps (ML Orchestration, Docker, Kubernetes, MLflow, etc.).

Mploy