Data Analyst, Technical Operations

We envision a future powered by robots that work seamlessly with human teams. We build the artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Our flagship robot, Moxi, works alongside clinical staff in hospitals every day — handling routine tasks so care teams can focus on patients. As our fleet and customer base grow, so does our need to make smart, data-driven decisions about how we operate, service, and scale.

We're looking for a curious, roll-up-your-sleeves Data Analyst to support our Technical Operations, Service Operations, and Customer Success teams. This is a great fit for a generalist who wants broad exposure and real ownership early on: you'll turn fleet, service, and customer data into the insights that shape how we keep robots running, how we prioritize what to fix, and how we build a service organization that scales with the company.

You'll help lay the data foundation for a planned maintenance program, inform where we invest as we grow, and give our teams a clear, shared picture of what's actually happening in the field. If you like variety, ambiguity, and seeing your analysis translate directly into operational decisions, this role is for you.

• →Build and maintain dashboards and reporting that give a clear, shared view of fleet performance and key metrics across teams.
• →Analyze fleet, service, and customer data to surface trends, recurring issues, and opportunities to improve.
• →Provide the data to support a planned maintenance program, smarter issue prioritization, and a scalable service organization.
• →Partner with Technical Operations, Service Operations, and Customer Success to answer time-sensitive questions and inform decisions.
• →Automate recurring reporting and help maintain data quality, definitions, and documentation as our systems mature.
• →Communicate findings clearly to technical and non-technical audiences, and make recommendations people can act on.

• Bachelor's degree in a quantitative or technical field (e.g., data science, statistics, engineering, computer science, mathematics, economics) — or equivalent practical experience.
• 1–3 years of experience in a data, analytics, or operations role (strong internship or project experience counts).
• Working proficiency in SQL (experience with PostgreSQL preferred) and Python for analysis and automation.
• Proficiency with AI-assisted tools (e.g., Claude / Claude Cowork) to accelerate analysis, reporting, and problem-solving.
• Comfort with Google Workspace tools, especially Google Sheets.
• Experience with — or a strong ability to quickly learn — a BI / data visualization tool (Looker, Tableau, Power BI, or similar).
• Strong analytical and problem-solving skills, with an ability to structure ambiguous questions and follow the data to an answer.
• Clear written and verbal communication, especially the ability to explain data to non-technical stakeholders.
• A self-starter mindset and genuine comfort wearing many hats in a fast-paced, changing environment.

• Experience with PostgreSQL and the Google product ecosystem (Google Sheets, Apps Script, BigQuery, etc.).
• Exposure to robotics, hardware, IoT, or other telemetry / time-series / fleet data.
• Understanding of service or reliability concepts — MTTR, uptime/availability, SLAs, preventive maintenance.
• Interest in or exposure to healthcare or hospital environments.