Data Scientist (Perception Verification and Validation)

Join Zoox, a leading autonomous driving company, as a Data Scientist in the Perception Verification and Validation team. In this role, you will work closely with data scientists, perception engineers, and systems engineers to develop datasets and metrics to quantify the performance of our perception system. You will also help define key performance metrics, create and maintain datasets, analyze large scale metric results, and design and implement statistical methods to quantify uncertainty in our performance and validation metrics. Enjoy a range of benefits including paid parental leave, health insurance, and a comprehensive wellbeing program.

• Definir métricas de rendimiento clave que ayudarán a los ingenieros de percepción a medir el impacto de nuevas características en el sistema de percepción.
• Crear y mantener conjuntos de datos utilizados para evaluar el sistema de percepción y el rendimiento de conducción de extremo a extremo.
• Analizar resultados métricos a gran escala para identificar patrones y obtener información sobre los modos de falla de percepción.
• We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team
• 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
• You do not need to match every listed expectation to apply for this position
• Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code
• Master's or PhD degree in Statistics, Mathematics, Computer Science, or a related field
• Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business
• Background in statistical modeling and analysis; including experience making data-driven decisions that connect point and uncertainty estimates to business impact
• Basic experience with autonomous driving, safety-critical systems, or computer vision systems
• Skilled at using AI tools to improve development efficiency and quality
• Experience analyzing geospatial data
• Experience with experiment design and statistical comparisons (A/B testing, parametric/non-parametric statistics, etc.)