Senior Data Scientist - Verification & Validation

What you'll do

• Develop rigorous evaluation frameworks, metrics, and validation methods for safety-critical AI systems.
• Analyze driving data to identify edge-case failures and communicate findings to engineering teams and executives.
• Build and maintain scalable data-processing and simulation pipelines for petabytes of driving data.

What they ask for

• MS or PhD in Statistics, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
• Proficiency in Python and SQL, with experience writing production-quality code.
• Expertise in statistical methods including hypothesis testing, power analysis, spatiotemporal modeling, Bayesian inference, and multivariate analysis.
• Experience with large-scale data analysis and statistical modeling; proficiency with Git, unit testing, and collaborative development practices.

Nice to have

• Hands-on experience with production machine learning pipelines, including dataset creation, training frameworks, and metrics pipelines.
• Experience with Apache Spark, Spark SQL, or Databricks; experience designing metrics and delivering actionable business insights.

Pay

USD 209,000–285,000 per-year-salary (base salary)

Tools

Python, SQL, Git, Apache Spark, Spark SQL, Databricks

AI focus

Evaluate safety-critical AI systems through statistical validation, analysis of potential edge-case failures, and development of evaluation pipelines.