Data Analyst, Supply Chain

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity. Who We Are We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully. The Data Analyst drives data management workflows and performs data analysis. This role connects our internal systems with various logistics partners, builds data pipelines, calculates metrics, and creates dashboards & alerts to highlight operational bottlenecks. This position leverages AI tools and frameworks to build faster, create scalable API connections, and manage the data architecture that keeps Serve’s supply chain running. JOB DUTIES Develop and manage API-based workflows to ensure seamless communication between our core business platforms and external logistics partners. Design, build, and maintain automated pipelines to retrieve and route data across various internal and external databases and tools. Perform hands-on data analysis (e.g., tracking average shipping times, inventory flows, etc.) and build automated spreadsheets and/or dashboards for stakeholders. Implement error handling, alerting, etc. to ensure data workflows run consistently and accurately. Partner with Supply Chain, Operations, Finance, and Engineering stakeholders to define KPIs, reporting requirements, and data quality standards across supply chain processes. Conduct root cause analysis on operational issues and recommend process improvements that reduce cost, improve inventory accuracy, and increase logistics performance. Create and maintain technical documentation for data models, integrations, workflows, and reporting systems to support long term scalability and knowledge sharing. EXPERIENCE, QUALIFICATIONS, & SKILLS Required Experience, Qualifications, and Skills 5 years of hands-on experience in data analysis, data engineering, workflow automation, or similar technical roles. Strong general knowledge of data structures and data management, both for big data using cloud databases and small data using excel & google sheets. Advanced knowledge of SQL and at least one other programming language (ideally Python or Javascript). Proficiency in modern AI-driven development including AI coding tools (e.g., Claude Code, GitHub Copilot, Codex), Model Context Protocol (MCP), configuration of Skills, sub-agents, etc. and familiarity with popular AI orchestration frameworks such as Langgraph, OpenAI API/SDK, Gemini API/SDK, etc. Experience designing data models and transforming data from multiple operational systems into clean, reliable datasets for reporting and analysis. Strong analytical and problem solving skills, with the ability to translate complex data into actionable business recommendations for nontechnical stakeholders. Demonstrated ability to independently manage multiple projects, prioritize competing requests, and deliver high quality work in a fast paced environment. Preferred Experience, Qualifications, and Skills Google Cloud Platform (GCP): Specifically Cloud Run, BigQuery, and other supporting services. Google Workspace / G Suite: Specifically Google Sheets and Google Apps Script. NetSuite: Specifically working with the NetSuite API. Supply Chain Tech Experience: Applying these data and technology skills specifically within supply chain, logistics, or e-commerce operations. Experience working with third party logistics (3PL), fulfillment, inventory management, or transportation management systems. Familiarity with data observability, monitoring, and data quality frameworks in production environments.