Sr Staff Data Scientist

Palo Alto Networks-posted 1 day ago
Full-time • Mid Level
Hybrid • Santa Clara, CA
5,001-10,000 employees
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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.

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