Staff Data Scientist

5 Days ago • 5 Years +

Data Analysis

Job Description

As a Staff Data Scientist at CyberArk, you will drive AI/ML projects from research to production, developing innovative AI/ML solutions to enhance identity security and protect against emerging threats. This role involves designing, implementing, and optimizing machine learning models using frameworks like PyTorch and TensorFlow, collaborating with product managers and engineers, and translating business needs into actionable AI/ML roadmaps. You will need a minimum of 5 years of experience in AI/ML and Data Science, or a PhD with 3 years, along with a Master's or PhD in a quantitative field.

Good To Have:

Experience with AWS ecosystem (SageMaker, Glue, Athena, Redshift, EMR) and Spark.
Background in cyber security.

Must Have:

Drive AI/ML projects from research to production, leveraging advanced algorithms, LLMs, classification models, Unsupervised learning and optimization techniques to enhance cybersecurity solutions.
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.
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.

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

team-player

game-texts

aws

spark

data-science

scikit-learn

pytorch

deep-learning

algorithms

tensorflow

machine-learning

##### 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 X, 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-Hybrid

#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

##### Additional Information

How you will stand out from the crowd: