Senior Data Analyst, Operations

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit:

As a member of Waabi's Operations organization, the Senior Data Analyst will own and evolve the metrics, dashboards, and analytical foundations used to understand and operate the fleet. This role is critical to ensuring our operational data is accurate, consistent, and actionable across fleet performance, utilization, uptime, operational readiness, and commercial reporting. We need someone who will take initiative, live and breathe the data, and come forward with ideas on what metrics to explore, what patterns matter, and where operational performance can improve. This role is not just about reporting on the business, it is about helping shape how the business operates through data-backed insight.

You will…

• Define, implement, track, manage, and continuously improve core operational metrics used to measure 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, validate their completeness and integrity, partnering with Data Platform on upstream pipelines and infrastructure.
• Build, maintain, and standardize dashboards and recurring reporting across operations to ensure accuracy, consistency, and alignment with business needs, converting manual tracking and fragmented reporting into automated workflows.
• Analyze productivity, delays, downtime, and other operational inefficiencies to identify trends, root causes, and improvement opportunities.
• Proactively propose new metrics, dashboards, and analyses based on what the data is showing, not only on predefined requests.
• Quantify the impact of operational issues, including lost hours, miles, missions, and other business-critical outputs.
• Build structured tracking across the mission lifecycle, including pre-mission, in-mission, and post-mission performance.
• Support internal and external reporting for commercial operations and demos, including metrics such as completion rates, cancellations, and execution quality.
• Identify data gaps, quality issues, and inconsistencies across systems, and recommend scalable improvements.
• Partner closely with Ops, Commercial, Data Platform, and other stakeholders to clarify requirements and deliver actionable insight.
• Help convert manual tracking and fragmented reporting into reliable, scalable datasets and automated reporting workflows.

Qualifications:

• Bachelor's degree in Data, Statistics, Computer Science, Engineering, or a 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 working with relational datasets, plus experience with Python or R for analysis, pandas preferred.
• Familiarity with dbt (data build tool) and modern analytics workflows for modeling and transforming data.
• Experience cleaning, validating, reconciling, and analyzing data from multiple sources.
• Experience building dashboards and recurring reports using BI tools, with the ability to quickly adopt new analytics and AI-assisted tools and workflows.
• Strong statistical literacy, with demonstrated ability to apply methods like significance testing, regression analysis, and distribution analysis in order to identify the true drivers of performance.
• Strong problem-solving skills, sound business judgment, and the ability to independently turn ambiguous questions into structured analysis, surface insights, and make recommendations.
• Strong communication skills and the ability to translate data into clear takeaways for operational and leadership audiences.

Bonus:

• Experience working with operations, logistics, fleet, transportation, or other operationally complex datasets, including customer-facing or commercial reporting.
• Experience with modern analytics and operational tooling, including cloud data warehouses, ETL or API-based ingestion, workflow automation, operational systems, and evaluation or adoption of new analytical or AI-assisted tools.