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Waabi is a Physical AI company founded by AI visionary Raquel Urtasun, leading the autonomous transportation space with commercial autonomous trucks and robotaxis. The company is backed by world leaders in AI, automotive, logistics, and deep tech, with offices in Toronto, San Francisco, Dallas, and Pittsburgh.
As Senior Data Analyst in Operations, you will own and evolve the metrics, dashboards, and analytical foundations that drive fleet operations. This is a strategic role focused on ensuring operational data is accurate, consistent, and actionable across fleet performance, utilization, uptime, operational readiness, and commercial reporting. You will take initiative to identify what metrics matter, uncover patterns, and drive operational improvements through data-backed insights.
Key responsibilities include:
- Define, implement, track, manage, and continuously improve core operational metrics for fleet performance, efficiency, utilization, uptime, and readiness
- Build and maintain data pipelines, analytical datasets, data models, and automated workflows that consolidate operational data from multiple sources, validating completeness and integrity
- Partner with Data Platform on upstream pipelines and infrastructure
- Build, maintain, and standardize dashboards and recurring reporting across operations, converting manual tracking into automated workflows
- Analyze productivity, delays, downtime, and operational inefficiencies to identify trends, root causes, and improvement opportunities
- Proactively propose new metrics, dashboards, and analyses based on data insights
- Quantify the impact of operational issues including lost hours, miles, and missions
- Build structured tracking across the mission lifecycle (pre-mission, in-mission, post-mission)
- Support internal and external reporting for commercial operations and demos
- Identify data gaps, quality issues, and inconsistencies, recommending scalable improvements
- Partner closely with Ops, Commercial, Data Platform, and other stakeholders
Requirements:
- Bachelor's degree in Data, Statistics, Computer Science, Engineering, or related field, or equivalent practical experience
- 3–5 years of experience in a dedicated data analyst, analytics, or business intelligence role
- Strong SQL skills and experience with relational datasets
- Experience with Python or R for analysis (pandas preferred)
- Familiarity with dbt (data build tool) and modern analytics workflows
- Experience cleaning, validating, reconciling, and analyzing data from multiple sources
- Experience building dashboards and recurring reports using BI tools; ability to quickly adopt new analytics and AI-assisted tools
- Strong statistical literacy with demonstrated ability to apply significance testing, regression analysis, and distribution analysis
- Strong problem-solving skills, sound business judgment, and ability to turn ambiguous questions into structured analysis
- Strong communication skills and ability to translate data into clear takeaways for operational and leadership audiences
Bonus qualifications:
- Experience with operations, logistics, fleet, transportation, or operationally complex datasets
- Experience with customer-facing or commercial reporting
- Experience with modern analytics and operational tooling including cloud data warehouses, ETL, API-based ingestion, workflow automation, and operational systems
