Senior Data Scientist - Verification & Validation

Design Evaluation Frameworks: Architect statistical methodologies for safety-critical AI systems to form objective, rigorous conclusions about their performance and reliability.

Conduct Robust Analysis: Deliver validation evidence to support increasingly complex operations and identify potential edge-case failures.

Inform Strategy: Deliver clear, data-driven insights to development teams to guide system improvement, and to executive leadership to inform milestone-level go/no-go decisions.

Define Metrics: Drive alignment across engineering teams on performance metrics and data extraction strategies.

Lead the Lifecycle: Manage all phases of evaluation including prototyping, requirements capture, design, implementation, and validation.

Scale Pipelines: Partner with engineers to build and maintain scalable data processing and simulation pipelines, applying distributed computing to analyze petabytes of driving data.

Hands-on experience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelines

Experience with modern data processing technologies such as Apache Spark, Spark SQL, and Databricks