Ticketing Insights Analyst II

In-person Interview Requirement

Candidates must be willing to participate in at least one in-person interview.

This role serves as the analytical backbone of the Wireless Ticketing Insights team, converting complex, unstructured ticketing data into prioritized, quantified problem statements that drive strategic business decisions. Operating within a rigorous six-step pipeline—Detect, Size, Diagnose, Route, Validate, and Report—this position diagnoses root causes of operational friction and routes validated insights to cross-functional resolution teams. The primary challenge involves translating fragmented data and operational "noise" into clear, actionable narratives that proactively prevent customer pain and streamline ticket processes.

By leveraging cutting‑edge AI and machine learning capabilities, the role architects automated, preventative solutions that move the department beyond simple manual reporting.

• Spearhead complex data analysis projects to identify the upstream product, process, or system issues driving preventable ticket volume and translate raw operational data into evidence‑backed diagnoses.
• Monitor and manage critical ticketing metrics using statistical methods to detect emerging spikes and anomalies early, quantifying their business impact before escalation.
• Architect automated workflows and predictive models using AI‑augmented analytics, including Snowflake Cortex, to accelerate speed‑to‑insight and reduce manual data processing.
• Collaborate with cross‑functional partners to route validated insights to the correct owners and track resolution outcomes to ensure measurable improvements in customer experience.
• Organize and present highly complex findings as clear, actionable narratives to both technical teams and senior leadership to secure alignment on resolution strategies.
• Deliver quantifiable results tied directly to department OKRs, specifically driving ticket volume reduction, process efficiency, and operational cost savings.

• Strong skills in querying large datasets, investigating raw records, and transforming unstructured or noisy operational data into analysis‑ready outputs using advanced SQL.
• Expertise in leveraging modern cloud‑based analytics platforms to build automated visualizations, surface insights, and develop compelling data‑driven business cases.
• Demonstrated capability in translating complex artificial intelligence and machine learning concepts, including agentic AI and LLM workflows, into actionable intelligence for non‑technical leadership.
• Proactive problem‑solving abilities and a self‑starter mindset to navigate ambiguous scopes, managing both immediate requests and long‑term strategic projects.
• Exceptional data storytelling and presentation skills, with the professional capability to drive alignment and collaboration across cross‑functional business partners.
• Advanced AI literacy, including practical experience incorporating knowledge‑based Retrieval‑Augmented Generation (RAG) and prompt engineering into analytical workflows.

• Programming experience in Python or an equivalent scripting language to build advanced analytical models.

• Minimum Education:
  
  Bachelor’s Degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related quantitative discipline (or 2+ years of equivalent practical experience).
• Minimum Experience:
  
  2 years of experience in data analytics, business intelligence, or operational reporting.
• Required Technical
  
  Skills:
  • Advanced SQL query development and database management.
  • Cloud‑based analytics platforms and data visualization tool design.
  • AI‑assisted analytics tools or machine learning applications.

Visa sponsorship not available for this role.

Compensation: $63,150.00/Year - $90,000.00/Year

We offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan.

The base pay range shown is a guideline. Individual total compensation will vary based on factors such as…