Data Analyst, Autonomy

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 while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

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.

Join Serve Robotics as our Senior Analyst to revolutionize the future of autonomous last-mile delivery. In this role, you'll work cross-functionally to uncover insights, optimize processes, and drive strategic decisions to fuel our rapid growth. You’ll thrive in a dynamic, fast paced environment—balancing deep analytical rigor and competing priorities to deliver impactful recommendations.

As a key member of the analytics team, you'll help define how we measure success, guide new market expansion, and continuously improve Fleet operations. Your curiosity and ability to turn messy data into actionable insights will be essential and will directly influence real-world operations.

• Analyze extensive data from robot operations to identify key factors causing stoppages and performance issues.

• Develop methodologies to slice and dice data meaningfully, uncovering trends and insights that inform decision-making.

• Support the autonomy team by providing data-driven insights on system performance, failures, and optimization opportunities.

• Identify interesting trends beyond core operational issues to help shape the long-term autonomy roadmap.

• Define, manage, and refine key performance indicators (KPIs) for feature development and deployment.

• Ensure that KPIs and metrics are well-maintained, statistically significant, and meaningfully contribute to product improvements.

• Work closely with engineering and product teams to ensure that features achieve their intended outcomes through well-designed metrics. Establish statistical methodologies to evaluate the significance and reliability of collected data.

• Build and maintain dashboards and reporting tools to help engineering teams to get insights in robot performance

• Automate reporting processes to track feature effectiveness and operational performance over time.

• Provide visibility into KPIs across stakeholders, ensuring alignment on priorities and progress.

• Define frameworks to measure the statistical significance of metrics collected in production and testing environments.

• Determine if the current test coverage is an accurate representation of real-world scenarios and ensure sufficient data collection for validation.

• Assess how much data is required for statistically significant conclusions about autonomy features.

• Provide confidence intervals and statistical significance measures for KPI monitoring in production.

• Support A/B testing and experimental analysis for new autonomy features.

• 3+ years of experience in data modeling and analysis, preferably in robotics, autonomous systems, or logistics.

• Advanced Proficiency in SQL for data exploration, transformation, and analysis across large datasets

• Proven expertise in using data visualization and BI tools (e.g., Tableau, Looker) to communicate insights and support decision-making.

• Strong programming skills in Python or R for data manipulation and statistical analysis.

• Deep understanding of statistical analysis, hypothesis testing, and experimental design.

• Ability to clearly communicate data findings and help turn insights into practical next steps for stakeholders.

• Familiarity with machine learning concepts

• Experience working with autonomy teams and understanding robotic KPIs

• Basic understanding of data ingestion pipelines, data partitioning, and performance optimization in a cloud environment.