Data Scientist - Collision Avoidance System - Zoox

Job Title: Data Scientist - Collision Avoidance System
Job Location: Foster City, CA
Job Listing URL: https://jobs.lever.co/zoox/811b6406-523c-49f2-830b-3c1aaef4ebaa
Job Description: The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main Artificial Intelligence (AI) autonomy stack, and has a close relationship with our vehicle hardware and safety teams in order to architect redundancy into our overall driving system.
Responsibilities
You will define key performance metrics for our safety critical perception and prediction system, in order to guide product development to a commercial launch
You will work closely with software engineers, data engineers, and data scientists to develop metrics and tools for analyzing errors and guiding improvements in our systems
You will contribute to all phases of the software development cycle including prototyping, requirements capture, design, implementation, and validation
You will apply distributed computing algorithms to efficiently analyze petabytes of urban driving data
Qualifications
MS or PhD in Statistics, Computer Science, Machine Learning, Applied Mathematics, or related quantitative field
Proficiency in Python and SQL with experience in production-quality code
Demonstrated expertise in statistical methodologies including hypothesis testing, power analysis, spatiotemporal modeling, Bayesian inference, and multivariate analysis.
Experience with large-scale data analysis and statistical modelingProficiency with Git, unit testing, and collaborative development practices
Bonus Qualifications
Hands-on experience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelines
Experience with modern data processing technologies such as Apache Spark, Spark SQL, and Databricks
Experience with designing metrics and delivering actionable insights that drive business decisions

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