Field Reliability Data Analyst

Reliability is at the foundation of our autonomous vehicle platform. As a Field Reliability Data Analyst you will play a key role in building the data collection and analysis architecture from the ground up to support the continued improvement of fleet reliability here at Zoox. Working with Zoox reliability engineers, hardware design engineers, service operations and our L3 and L5 vehicle fleet teams you will be helping Zoox bring an innovative dense urban mobility service into reality.

Responsibilities

• Collaborate with Data Science, Service, IT, and other data stakeholders to create streamlined data interfaces that ensures the capture of data necessary for reliability analytics.
• Understand and incorporate field reliability concepts such as parametric and non-parametric lifetime data analysis, fleet/vehicle/system availability/unavailability estimation and forecasting, repairable/non-repairable system analysis, etc.
• Identify and utilize proper data sources to track usage of components or subsystems on the vehicle through time, and to draw conclusions about each unit’s failure rate and remaining useful life.
• Establish data pipelines and framework to retrieve and analyze field reliability data on the family of the same hardware/system across the fleet at any given time, and to make actionable recommendations based on company milestones.
• Lead the creation of data visualization tools to present the results of reliability analyses cross-functionally across Zoox.

Qualifications

• Minimum requirement is a Bachelor of Science in Engineering/Statistics/Applied Mathematics
• 5+ years of experience of field reliability experience
• Experience in reliability data analysis and data visualization techniques
• Expert in SQL and database organization
• Expert in Python and applicable packages such as Pandas, Numpy and Scipy
• Experience mining Jira projects for required data and information
• Hands-on experience with distributed version-control systems (Git)
• Familiarity with Spark or large-scale data analysis
• General knowledge of multivariable statistical inference techniques
• Excellent communication and collaboration skills

Bonus Qualifications

• Automotive field reliability/service experience
• Advanced degree in Engineering/Statistics/Applied Mathematics/Data Science Boot Camp certification
• Understanding of reliability failure mechanisms and damage models
• Experience with prognostic health monitoring
• Familiarity with Databricks

Vaccine MandateEmployees working in this position will be required to be fully vaccinated against the COVID-19 virus. An applicant is considered fully vaccinated two weeks after their second dose in a 2-dose series, such as the Pfizer or Moderna vaccines, or two weeks after a single-dose vaccine, such as Johnson & Johnson’s Janssen vaccine. Applicants will be required to show proof of vaccination status upon receipt of a conditional offer of employment. That offer of employment will be conditioned upon, among other things, an Applicant’s ability to show proof of vaccination status. Please note the Company provides reasonable accommodations in accordance with applicable state, federal and local laws.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.Follow us on LinkedInA Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.