Data Analyst – Autonomy

Data Analyst – Autonomy

Requirements

• 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.

Responsibilities

• 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.

Preferred Qualifications

• 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.