Senior Data Scientist

Company Description

About CyberArk:
CyberArk (NASDAQ: CYBR), is the global leader in Identity Security. Centered on privileged access management, CyberArk provides the most comprehensive security offering for any identity – human or machine – across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. The world’s leading organizations trust CyberArk to help secure their most critical assets. To learn more about CyberArk, visit our CyberArk blogs or follow us on Twitter, LinkedIn or Facebook.

Job Description

What will you do:

As Senior Data scientist at CyberArk, you will shape the future of identity security and develop innovative AI/ML solutions that enhance security and protect the emerging agentic AI landscape in top organizations. Drive AI research and engineering to address evolving threats and protect critical digital assets effectively.

• Drive AI/ML projects from research to production, leveraging advanced algorithms, LLMs, classification models, Unsupervised learning and optimization techniques to enhance cybersecurity solutions.
• Model Building: Design, implement, and optimize machine learning models, including deep learning, using frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
• Work closely with product manager, engineers, software architects and analysts to understand requirements, validate model assumptions, and deliver actionable insights.
• Identify AI/ML impact opportunities and translate business needs into actionable roadmap items.
• Stay current with the latest advancements in data science and apply best practices to ensure optimal performance

#LI-OS1

Qualifications

What you need to succeed:

• Minimum 5 years of relevant work experience in AI/ML and Data Science, or PhD with 3 years.
• Masters degree or PhD in a quantitative field – Computer Science, Mathematics, Statistics, Engineering etc.
• Hands-on experience with frameworks such as scikit-learn, PyTorch, Hugging Face, TensorFlow, or equivalent tools for model development and training.
• Proven ability to apply statistical modeling and machine learning methods to real-world problems, ideally in the context of cybersecurity or related fields.
• Proven track record of successfully taking AI/ML project inception to production
• Proficient in communicating technical ideas and collaborating effectively across teams and organizational stakeholders.
• Team player, responsible, accountable, delivery oriented and with a can do approach.

How you will stand out from the crowd: 

• AWS ecosystem (SageMaker, Glue, Athena, Redshift, EMR) and Spark - an advantage
• Background in cyber security – a strong advantage