Data Scientist Team Leader

2 Months ago • All levels
Data Analysis

Job Description

As a Data Science Team Leader at CyberArk, you will lead a high-performing team developing AI/ML solutions that secure the digital world’s most sensitive assets. You’ll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, you’ll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. You’ll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across CyberArk’s identity security portfolio.
Must Have:
  • Lead, mentor, and grow a team of applied data scientists
  • Own end-to-end development lifecycle of AI projects
  • Partner with engineering and product leadership
  • Drive innovation in ML domains
  • Provide hands-on guidance in model development
  • Ensure high-quality execution through code review
  • Champion best practices in MLOps
  • Translate cutting-edge research into productized capabilities

Add these skills to join the top 1% applicants for this job

data-science
scikit-learn
pytorch
tensorflow
machine-learning

As a Data Science Team Leader at CyberArk, you will lead a high-performing team developing AI/ML solutions that secure the digital world’s most sensitive assets. You’ll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, you’ll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. You’ll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across CyberArk’s identity security portfolio.

  • Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
  • Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
  • Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
  • Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
  • Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
  • Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
  • Champion best practices in MLOps, data governance, explainability, and monitoring.
  • Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

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