Data Scientist, Metrics Team

Overview

Established in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level
4. WeRide is the only tech company in the world that holds driverless permits in China, the UAE, Singapore and the US, conducting autonomous driving R&D, tests and operations in over 30 cities of 10 countries around the world. WeRide has operated a self-driving fleet for more than 2,200 days.

WeRide.ai Silicon Valley team is looking for an experienced and innovative data scientist for its growing metrics team to support the development and validation of both L3+ Advanced Driver Assistance Systems (ADAS) and L4 Autonomous Driving (AD) Systems. The level depends on the candidate s experience and qualification.

The metrics team is at the forefront of accelerating the development and deployment of cutting-edge ADAS/AV technologies. As a Senior Data Scientist on this team, you will play a pivotal role in ensuring the safety, reliability, and efficiency of our autonomous systems. You will be responsible for developing and implementing rigorous evaluation frameworks and advanced statistical methodologies to assess overall system performance, as well as the performance of critical sub-systems across software releases, and different territories.

Your work will directly inform crucial engineering decisions, guide iterative improvements, and contribute to the successful commercialization of our ADAS/AV stack.

• Develop Rigorous Evaluation Frameworks:
  Design, develop, and implement advanced statistical frameworks for the comprehensive evaluation of ADAS/AV system performance, with a strong emphasis on safety, compliance, and progress metrics
• Define and Monitor System Performance:
  Define, measure, and monitor key performance indicators (KPIs) for the overall ADAS/AV system. Develop automated data pipelines and reporting mechanisms to track these metrics across software releases
• Evaluate Sub-system Performance:
  Define and implement metrics to evaluate the performance of individual sub-systems. Utilize these metrics to provide actionable insights that guide and accelerate sub-system development and improvement
• Statistical Analysis and Experimentation:
  Apply advanced statistical techniques, including hypothesis testing, experimental design, and causal inference, to analyze complex behavioral data and derive robust insights into system performance and regressions between releases
• Partner with Engineering Teams:
  Collaborate closely with Simulation, Systems Engineering, Product, and Software Development teams to integrate evaluation insights into the development lifecycle, inform release readiness, and ensure alignment on performance targets
• Technical Leadership and Mentorship:
  Provide technical leadership on complex data science problems, champion best practices in data analysis and statistical rigor, and mentor junior data scientists within the team
• Data Visualization and Communication:
  Create compelling data visualizations and communicate complex analytical findings clearly and concisely to diverse audiences, ranging from technical engineers to senior leadership

• Quantitative Degree:
  Master’s degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field
• Extensive Industry
  
  Experience:
  
  3+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models
• Advanced Statistical Expertise:
  Deep expertise in advanced statistical methods and their application in real-world settings, including experimental design, hypothesis testing, regression analysis, causal inference and time series analysis, etc
• Technical Problem Formulation:
  Proven ability to translate ambiguous real-world challenges into clearly defined data science problems, identify appropriate methodologies, and deliver effective solutions
• Data Manipulation and Analysis:
  Proficiency in using programming languages (e.g., Python, R) and SQL for data extraction, manipulation, and analysis
• Communication:
  Excellent verbal and written communication skills, with the ability to tailor technical explanations to various stakeholders
• Flexibility:
  Ability to collaborate effectively with teams in different time zones

• PhD degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field
• 5+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models
• Experience with large-scale evaluation frameworks for complex software systems, particularly in autonomous driving or robotics
• Familiarity with ADAS/AV system architectures and the behavioral challenges inherent in autonomous driving
• Knowledge of simulation platforms and their role in data generation and system evaluation

Salary Range:
Your base pay is one part of your total…