Senior 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 Senior 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.

While each day at Waymo is different, your primary responsibilities will include:

• Develop evaluation frameworks that are critical to ML model improvements.
• Design and implement robust data analysis pipelines and validation frameworks.
• Develop and apply statistical methods and ML models to analyze historical/simulation data
• Collaborate with cross-functional teams like Simulation and Planning to ensure consistent results across the autonomous driving system.

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

• PhD in a quantitative field (IE Statistics, Mathematics, Physics)
• 3+ 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 interpret and work with data in the presence of ambiguity (e.g., confounding factors, data sparsity or quality challenges)
• Demonstrated knowledge of Python/SQL/R data analysis libraries and packages
• Ability to take ambiguous and complex business requirements and propose a technical solution

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
• Hands-on experience with Google infra tools like PLX, Borg, GCL, etc

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