• Analyze large-scale telematics and execution data across fleets, lanes, and time • Identify patterns in capacity, utilization, dwell, reliability, HOS, and asset behavior • Develop metrics and summaries that reflect real-world freight performance • Build and maintain large-scale sandboxes (1,000+ vehicles) using masked or synthetic data • Create compelling examples for sales, pilots, and customer conversations • Partner with GTM to turn raw data into clear ROI stories and proof points • Surface data-driven insights that influence roadmap priorities • Validate assumptions about customer use cases with real network data • Help define “decision-grade” metrics that customers actually trust • Work closely with product, engineering, and FDEs to understand data nuances • Support pilots and strategic accounts (e.g., TMS, visibility, broker platforms) • Translate technical findings into clear narratives for non-technical audiences • Help define data quality checks, thresholds, and confidence measures • Assist in shaping normalized views (lane history, asset identity, availability) • Focus on interpretability and usability over black-box modeling