Staff Data Scientist - Behavior Evaluation

Overview

We are seeking a highly skilled and experienced Staff Data Scientist to join our Autonomy Software team and play a pivotal role in developing and deploying cutting-edge autonomous driving technologies. You will tackle complex data challenges, drive innovation in machine learning and statistical modeling, and contribute to the advancement of our self-driving systems.

Responsibilities

• Analyze large-scale datasets from various sources, such as fleet and simulation data, to extract actionable insights.
• Develop and evaluate novel algorithms and methodologies for data processing, feature engineering, model training, and performance optimization.
• Evaluate and validate model performance through rigorous testing and analysis, ensuring the safety and reliability of our systems.
• Communicate complex technical findings and recommendations to both technical and non-technical audiences.
• Mentor and provide technical guidance to junior data scientists and engineers.

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with 8+ years of experience as a Data Scientist.
• Strong programming skills in Python, including experience with relevant libraries such as scikit-learn, Pandas, and SQL.
• Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling.
• Experience working with large-scale datasets and distributed computing platforms (e.g., Spark, Hadoop) with a solid understanding of data processing, feature engineering, and data visualization techniques.
• Strong communication and presentation skills, with the ability to effectively convey technical information to diverse audiences.

Bonus Qualifications

• Experience working with autonomous driving data and algorithms, robotics, control systems, or related fields.
• Experience with real-time data processing and low-latency systems.
• Publications in top-tier machine learning or autonomous driving conferences.