Staff Data Scientist

Data, machine learning, and statistical models play a critical role in building the Waymo Driver and in evaluating its performance. Waymo data scientists work closely with engineering and ensure high-quality reasoning and validation about data and models in our production systems. We help our partner teams interpret data in the face of statistical uncertainty, data ambiguity, and systematic biases - for example, in the causal interpretation of observational data. We also develop metrics and experimental designs that capture key performance aspects of our autonomous systems. Examples of areas the data science team is deeply involved in include safety readiness evaluation, development of signals to characterize good driving, evaluation of ML models in production systems, and simulation technology (virtual driving).

As a Staff Data Scientist at Waymo, you'll play a critical role in ensuring the safety and reliability of autonomous vehicles. Your responsibilities will span the entire spectrum of data analysis, model development, and evaluation.

In this role you'll:

• Develop evaluation frameworks for both autonomous vehicle performance and the evaluation frameworks themselves ("eval of eval").
• Develop and apply statistical methods and ML models to analyze historical/simulation data.
• Frame and solve ambiguous problems and communicate the results effectively.
• Develop new metrics, interpret trends, and investigate anomalies in data from simulation as well as our rider-only service. Communicate effectively and persuasively with leadership about your findings.
• Interact cross-functionally; be a thought partner and influence collaborators across multiple teams.
• Mentor other data scientists, either formally (as a tech lead) or less formally (as an individual contributor).

At a minimum, we'd like you to have:

• PhD in a quantitative field (e.g. Statistics, Mathematics, Physics)
• 5+ years of industry experience solving large-scale, complex problems
• Proven expertise using advanced statistical methods (e.g., ML models, hypothesis testing, causal analysis)
• Ability to take ambiguous and complex problems and propose appropriate technical solutions.
• Demonstrated knowledge of Python/SQL/R data analysis libraries and packages
• Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.

It’s preferred if you have:

• Experience solving problems related to Autonomous Driving
• Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction
• People leadership experience a plus