Data Scientist, Metrics Team

What You Will Do:

• 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.

Requirements:

• 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.

Preferred Qualifications:

• 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.