Know ATS Score
CV/Résumé Score
  • Expertini Resume Scoring: Our Semantic Matching Algorithm evaluates your CV/Résumé before you apply for this job role: Staff Data Scientist, Full Stack.
United States Jobs Expertini

Urgent! Staff Data Scientist, Full Stack Job Opening In Santa Clara – Now Hiring Palo Alto Networks

Staff Data Scientist, Full Stack



Job description

Job Description

Your Career

As a Staff Data Engineer and Scientist, you will be an integral member of our Customer Analytics team, responsible for shaping the future of our business operations through robust data infrastructure and advanced analytical solutions.

This unique hybrid role combines data engineering and applied AI/ML, requiring an entrepreneurial problem-solver who thrives in tackling ambiguous business problems through their deep understanding of the business as well as deep technical expertise.

You will act as both a strategic partner as well as builder, developing deep insights , building, developing and curating new datasets, as well as owning the end to end ML/AI model deployment for key customer success initiatives.  

You will be constantly challenged by tough engineering and design tasks, working in a fast-paced setting to deliver high-quality, impactful work.

This is an in office role 3 days/week in our HQ, Santa Clara, CA

Your Impact

In this versatile role, you will drive impact across both data engineering and data science domains:

Data Engineering Foundations

  • Design & Development: Design and implement scalable data architectures and datasets that support the organization's evolving data needs, providing the technical foundations for our analytics team and business users. 

  • Data Engineering: Support and implement large datasets in batch/real-time analytical solutions leveraging data transformation technologies.

  • Data Security & Scalability: Enable robust data-level security features and build scalable solutions to support dynamic cloud environments, including financial considerations.

  • Process Improvement: Perform code reviews with peers and make recommendations on how to improve our end-to-end development processes.

AI/ML Innovation & Business Impact

  • Develop & Deploy Classical ML Models: Own the end-to-end lifecycle of machine learning projects.

    You'll build and productionize sophisticated models for critical business areas such as marketing attribution, customer churn prediction, case escalation and other relevant use-cases to post-sales. 

  • Optimize AI Agentic Systems: Play a key role in our generative AI initiatives.

    You will be responsible for characterizing, evaluating, and fine-tuning AI agents—such as conversational systems that allow users to query massive datasets using natural language—to improve their accuracy, efficiency, and reliability.

  • Partner with Business Stakeholders: Act as an internal consultant to our Go-to-Market (GTM), Global Customer Services (GCS) and Product and Finance teams.

    You'll translate business challenges into data science use-cases, identify opportunities for AI-driven solutions, and present your findings in a clear, actionable manner.

  • Own the Full Data Science Lifecycle: Your responsibilities will cover the entire project workflow, working with the business to understand the problem, charting a path to solve the problem, feature engineering, model selection and training, robust evaluation, deployment, and, in partnership with the data platform team, ongoing monitoring for performance degradation.


Qualifications

Your Experience 

  • 7 plus years experience building and maintain data pipeline both for reporting, analysis and feature engineering.

  • Experience building and optimizing clean, well-structured analytical datasets for business and data science use cases.

    This includes Implementing and supporting Big Data solutions for both batch (scheduled) and real-time (streaming) analytics.

  • Prior experience working extensively within dynamic cloud environments, specifically Google Cloud Services (GCS) BigQuery and Vertex AI.

  • Prior experience developing dashboards in Tableau/Looker or similar data viz platform.

  • Nice to have: Experience implementing and managing data-level security features to ensure data is protected and access is properly controlled.

  • Expert-level programming skills in Python and familiarity with core data science and machine learning libraries (e.g., Scikit-learn, Pandas, PyTorch/TensorFlow, XGBoost).

  • A solid command of SQL for complex querying and data manipulation.

  • Proven ability to work autonomously, navigate ambiguity, and drive projects from concept to completion.

Preferred Qualifications

  • Prior working experience in Customer Analytics space and customer experience use-cases, e.g. Escalation, Risk predictors, Renewals and efficiency of project delivery in Professional Services space.

  • Direct experience with generative AI, including hands-on work with LLMs and frameworks like LangChain, LlamaIndex, or the Hugging Face ecosystem.

  • Experience in evaluating and optimizing the performance of AI systems or agents.

  • Demonstrated expertise in specialized modeling domains such as causal inference, time-series analysis. 

  • An MS or PhD in a quantitative field like Computer Science, AI, Statistics, or equivalent practical experience or equivalent military experience.



Additional Information

The Team

Working at a high-tech cybersecurity company within Information Technology is a once-in-a-lifetime opportunity.

You’ll join the brightest minds in technology, creating, building, and supporting tools and enabling our global teams on the front line of defense against cyberattacks.



We’re connected by one mission but driven by the impact of that mission and what it means to protect our way of life in the digital age.

Join a dynamic and fast-paced team of people who feel excited by the prospect of a challenge and feel a thrill at resolving technical gaps that inhibit productivity.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location.

For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $143000- $231000/YR.

The offered compensation may also include restricted stock units and a bonus.

A description of our employee benefits may be found .  

 

Our Commitment



We’re problem solvers that take risks and challenge cybersecurity’s status quo.

It’s simple: we can’t accomplish our mission without diverse teams innovating, together.

We are committed to providing reasonable accommodations for all qualified individuals with a disability.

If you require assistance or accommodation due to a disability or special need, please contact us at  .

Palo Alto Networks is an equal opportunity employer.

We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.

All your information will be kept confidential according to EEO guidelines.


Is role eligible for Immigration Sponsorship?

No. 
Please note that we will not sponsor applicants for work visas for this position.


Required Skill Profession

Mathematical Science Occupations



Your Complete Job Search Toolkit

✨ Smart • Intelligent • Private • Secure

Start Using Our Tools

Join thousands of professionals who've advanced their careers with our platform

Rate or Report This Job
If you feel this job is inaccurate or spam kindly report to us using below form.
Please Note: This is NOT a job application form.


    Unlock Your Staff Data Potential: Insight & Career Growth Guide


  • Real-time Staff Data Jobs Trends in Santa Clara, United States (Graphical Representation)

    Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Staff Data in Santa Clara, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 74392 jobs in United States and 1005 jobs in Santa Clara. This comprehensive analysis highlights market share and opportunities for professionals in Staff Data roles. These dynamic trends provide a better understanding of the job market landscape in these regions.

  • Are You Looking for Staff Data Scientist, Full Stack Job?

    Great news! is currently hiring and seeking a Staff Data Scientist, Full Stack to join their team. Feel free to download the job details.

    Wait no longer! Are you also interested in exploring similar jobs? Search now: .

  • The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Palo Alto Networks adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:
    • 1. Independence
    • 2. Loyalty
    • 3. Impartiality
    • 4. Integrity
    • 5. Accountability
    • 6. Respect for human rights
    • 7. Obeying United States laws and regulations
  • What Is the Average Salary Range for Staff Data Scientist, Full Stack Positions?

    The average salary range for a varies, but the pay scale is rated "Standard" in Santa Clara. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

  • What Are the Key Qualifications for Staff Data Scientist, Full Stack?

    Key qualifications for Staff Data Scientist, Full Stack typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.

  • How Can I Improve My Chances of Getting Hired for Staff Data Scientist, Full Stack?

    To improve your chances of getting hired for Staff Data Scientist, Full Stack, consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

  • Interview Tips for Staff Data Scientist, Full Stack Job Success
    Palo Alto Networks interview tips for Staff Data Scientist, Full Stack

    Here are some tips to help you prepare for and ace your job interview:

    Before the Interview:
    • Research: Learn about the Palo Alto Networks's mission, values, products, and the specific job requirements and get further information about
    • Other Openings
    • Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.
    • Dress Professionally: Choose attire appropriate for the company culture.
    • Prepare Questions: Show your interest by having thoughtful questions for the interviewer.
    • Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.
    During the Interview:
    • Be Punctual: Arrive on time to demonstrate professionalism and respect.
    • Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.
    • Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.
    • Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.
    • Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.
    • Follow Up: Send a thank-you email to the interviewer within 24 hours.
    Additional Tips:
    • Be Yourself: Let your personality shine through while maintaining professionalism.
    • Be Honest: Don't exaggerate your skills or experience.
    • Be Positive: Focus on your strengths and accomplishments.
    • Body Language: Maintain good posture, avoid fidgeting, and make eye contact.
    • Turn Off Phone: Avoid distractions during the interview.
    Final Thought:

    To prepare for your Staff Data Scientist, Full Stack interview at Palo Alto Networks, research the company, understand the job requirements, and practice common interview questions.

    Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Palo Alto Networks's products or services and be prepared to discuss how you can contribute to their success.

    By following these tips, you can increase your chances of making a positive impression and landing the job!

  • How to Set Up Job Alerts for Staff Data Scientist, Full Stack Positions

    Setting up job alerts for Staff Data Scientist, Full Stack is easy with United States Jobs Expertini. Simply visit our job alerts page here, enter your preferred job title and location, and choose how often you want to receive notifications. You'll get the latest job openings sent directly to your email for FREE!