Senior Data Scientist - Machine Learning (Cortex)
@ Palo Alto Networks

Tel Aviv, Tel-Aviv District, Israel
On Site
Full-time
Posted 10 days ago

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Job Details

Company Description

Our MissionAt Palo Alto Networks® everything starts and ends with our mission: Being the cybersecurity partner of choice, protecting our digital way of life.

Our vision is a world where each day is safer and more secure than the one before.

We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

Who We Are

We take our mission of protecting the digital way of life seriously.

We are relentless in protecting our customers and we believe that the unique ideas of every member of our team contributes to our collective success.

Our values were crowdsourced by employees and are brought to life through each of us everyday - from disruptive innovation and collaboration, to execution.

From showing up for each other with integrity to creating an environment where we all feel included.

Your Career

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats?

Do you thrive in the dynamic world of cybersecurity?

If so, we invite you to join our innovative and forward-thinking team at Palo Alto Networks, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.

As a Senior Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new defense techniques against cyber-villains.

You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin.

Your Impact

  • Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
  • Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data.
  • Decompose complex problems scientifically and provide actionable insights and recommendations.
  • Lead and collaborate on end-to-end projects within the team and across engineering and product teams.

Qualifications

Your ExperienceNatural scientific curiosity and ability to handle complex problems.

At least 6 years of experience in hands-on data science projects.

High proficiency in python and at least good familiarity with SQL.

Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field or equivalent military experience required.

Deep understanding of probability, statistics, and machine learning models with a proven track record.

Demonstrated ability to run end-to-end research POCs.

Good communication skills, with the ability to convey complex research findings.

Preferred

Background in the cybersecurity domain.

Experience with recommender systems.

Experience working with big data platforms (e.g., GCP).

Experience with LLM-based algorithm design.

Familiarity with cloud-native architectures and services for data processing.

How to Get Hired at Palo Alto Networks

🎯 Tips for Getting Hired

  • Research Palo Alto Networks' culture: Study their mission, values, and recent news to align your application.
  • Customize your resume: Tailor your experience to emphasize relevant data science and cybersecurity skills.
  • Prepare for technical interviews: Brush up on Python, SQL, and machine learning concepts.
  • Showcase your problem-solving abilities: Prepare examples demonstrating your analytical skills and project experiences.

📝 Interview Preparation Advice

Technical Preparation

Deep dive into Python for data analysis.
Familiarize with SQL for database queries.
Work on machine learning algorithms practically.
Explore big data platforms like GCP.

Behavioral Questions

Prepare your story of tackling complex problems.
Consider how you've driven team collaboration.
Think of a time you adapted to change.
Reflect on your communication of technical findings.

Frequently Asked Questions