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Senior Data Analyst – GTM Operations and Analytics – Unit

Senior Data Analyst – GTM Operations and Analytics – Unit

CompanyPalo Alto Networks
LocationSanta Clara, CA, USA
Salary$Not Provided – $Not Provided
TypeFull-Time
Degrees
Experience LevelSenior

Requirements

  • Strong proficiency in Python, SQL, and data visualization tools (Tableau, Looker)
  • Hands-on experience with machine learning, statistical modeling, and optimization techniques
  • Experience with end-to-end data pipelines (ETL, feature engineering, model deployment)
  • 3-4 years of experience in data analytics/data science field required
  • Ability to translate complex data into executive-ready insights
  • Strong problem-solving and mathematical modeling skills

Responsibilities

  • Apply machine learning, predictive modeling, and statistical analysis to solve business challenges and optimize GTM performance
  • Develop optimization algorithms (e.g., linear programming) to improve resource allocation, pricing strategies, and operational efficiency
  • Leverage feature engineering and data mining to extract actionable insights from large datasets
  • Identify and implement process improvements to enhance efficiency across GTM functions
  • Automate workflows and reporting using Python, SQL, and Google Cloud tools
  • Build and maintain KPI dashboards (Tableau, Looker) to track business performance
  • Serve as a trusted advisor to GTM leadership, providing data-driven recommendations for strategic decision-making
  • Conduct deep-dive analyses to uncover trends, forecast outcomes, and inform planning
  • Partner with Product, Engineering, Finance, and Sales to align data initiatives with business goals
  • Support security transformation programs by analyzing data and improving processes
  • Manage a portfolio of analytics and operations projects, ensuring timely delivery and measurable impact

Preferred Qualifications

  • (Bonus) Familiarity with Google Cloud, AI/LLMs, and big data technologies
  • Experience in SaaS/subscription business models (preferred)