Sr Staff Data Scientist at Palo Alto Networks

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

22 Feb, 26

Salary

228050.0

Posted On

24 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, AI, Statistical Analysis, Predictive Modeling, Data Storytelling, Feature Engineering, Causal Inference, Time-Series Analysis, Marketing Mix Modeling, Generative AI, LLMs, LangChain, Hugging Face, Data Visualization, Collaboration

Industry

Computer and Network Security

Description

Company Description Our Mission At 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. As a member of our team, you will be shaping the future of cybersecurity. We work fast, value ongoing learning, and we respect each employee as a unique individual. Knowing we all have different needs, our development and personal wellbeing programs are designed to give you choice in how you are supported. This includes our FLEXBenefits wellbeing spending account with over 1,000 eligible items selected by employees, our mental and financial health resources, and our personalized learning opportunities - just to name a few! At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work full time from our office with flexibility offered where needed. This setup fosters casual conversations, problem-solving, and trusted relationships. Our goal is to create an environment where we all win with precision. Job Description Your Career We are seeking a versatile Data Scientist to join our team and help shape the future of our business operations. This role is a unique hybrid of classical machine learning and applied AI. You will tackle diverse and impactful projects, from building predictive models that drive key business decisions to characterizing and optimizing the performance of our emerging AI agentic systems. You are an entrepreneurial problem-solver who thrives in ambiguous environments and enjoys bridging the gap between technical execution and business strategy. In this role, you will act as both a builder, developing and deploying ML models, and a strategic partner, consulting with business teams to unlock new opportunities with data and AI. If you are passionate about wearing multiple hats, working in a fast-paced setting, and delivering high-quality, impactful work, we want to hear from you. This is an in-office role 3 days/week in our HQ, Santa Clara, CA. Your 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, and finance forecasting. 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 marketing, product, finance and go-to-market teams. You'll translate business challenges into data science problems, 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, chart 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. Data Storytelling: Don’t just build the model; sell the solution. You will visualize your findings (using Tableau, Looker, or custom coding) to make complex data intuitive for business stakeholders. Collaboration: Partner closely with Marketing and Product teams to translate their business goals into technical data requirements. Qualifications Your Experience Education & Experience: Bachelor’s degree with 5+ years of related experience; OR Master’s degree with 3+ years of related experience; OR PhD in a quantitative field (Computer Science, AI, Statistics, Physics, etc.) with 1+ years of experience (academic research applies). Strong foundation in statistics and probability theory and commonly used data science algorithms. Proven hands-on experience building and deploying machine learning models in a production environment. Preferred 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, or marketing mix modeling. 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 $141,000 - $228,050/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here. 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 [email protected]. 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.

Responsibilities

Develop and deploy machine learning models for critical business areas and optimize AI systems. Partner with business stakeholders to translate challenges into data science problems and present actionable findings.