Note: The job is a remote job and is open to candidates in USA. Palo Alto Networks is a cybersecurity company dedicated to protecting the digital way of life. As a Staff Data Engineer and Scientist, you will play a crucial role in the Customer Analytics team, focusing on building robust data infrastructure and advanced analytical solutions to tackle complex business problems.
Responsibilities
- 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
- Support and implement large datasets in batch/real-time analytical solutions leveraging data transformation technologies
- Enable robust data-level security features and build scalable solutions to support dynamic cloud environments, including financial considerations
- Perform code reviews with peers and make recommendations on how to improve our end-to-end development processes
- 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
- 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
- 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
- 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
Skills
- 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
- Expert-level programming skills in Python
- 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 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
Benefits
- Medical
- Dental
- Vision
- 401K
Company Overview