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Pano AI is seeking an Operations Data Analyst to support the Platform Intelligence Center (PIC) Ops team during a period of rapid growth in wildfire detection and response operations. The role combines technical analytics work with deep operational context—you'll own Metabase dashboards, SQL queries, and self-serve tools that individual contributors and leadership rely on daily to manage wildfire detection operations.
You will investigate vendor and agent performance across multiple review vendors, catching data quality issues early and maintaining metric consistency as operations scale. Key responsibilities include root-cause analysis of performance anomalies using hypothesis-driven approaches, forecasting staffing needs by analyzing historical incident volume and seasonality, and incorporating external data sources like fire activity and weather patterns to improve forecasts. You'll analyze headcount and coverage against demand to support scenario planning for peak wildfire season.
This role requires both technical strength (SQL, dbt, Metabase) and operational curiosity. You'll spend time understanding how PIC Ops actually works day-to-day—observing agent workflows, sitting with team members to understand real processes—rather than working solely from behind a query editor. You'll partner with the Analytics team to submit clear, well-scoped requests when fixes require changes to underlying data models or warehouse tables. Documentation for both technical and non-technical audiences is essential. The role includes occasional travel to international vendor sites to observe operations firsthand and bring those insights back into your analysis and tooling.
Pano AI is a Series B climate tech company backed by $89M in funding, recognized by Fast Company as a Top 10 Most Innovative AI Company and by TIME as one of the 100 Most Influential Companies of 2025. The company operates a network of AI-powered wildfire detection systems across North America and Australia, monitoring over 50 million acres worldwide.
