Senior Safety Data Scientist

Ieee Ru Sb; Pittsburgh, Northern (Allegheny County, KY); Hybrid; USD 134,000 - 234,000; Full time

Job summary

Aurora Operations, Inc. in Pittsburgh, PA seeks a Senior Safety Data Scientist to lead safety analyses and develop data-driven processes for autonomous vehicle safety programs.

You will design and deploy safety data pipelines, build models, and collaborate with cross-functional teams to translate complex findings into actionable risk mitigation strategies, with strong AWS and DBT experience preferred.

Qualifications

• Bachelor's degree required in statistics, math, physics, engineering, CS, or related field.
• At least 5 years of data science experience.
• Proficiency in Python and R.
• Experience deploying models on AWS.
• Experience with DBT, SQL, and data warehouses.
• Ability to analyze large datasets and visualize results.

Responsibilities

• Performs safety analyses and develops safety processes for autonomous vehicle programs.
• Designs and deploys data pipelines, models, and safety tooling.
• Leads quantitative risk assessments and safety reporting.
• Presents findings to technical and non-technical audiences.
• Ensures regulatory safety compliance and integrates risk measures.

Skills

Applied statistics

Python

R

SQL

Data visualization

Machine learning

Data pipelines

Education

Bachelor's degree

Tools

AWS

DBT

SQL

Job description

Company Name: Aurora Operations, Inc.

Job Location: 50 33rd Street, Pittsburgh, PA 15201

Job title: Senior Safety Data Scientist

Salary: $134,000 - $234,000 per year

Education: Bachelor’s degree in Statistics, Mathematics, Physics, Engineering, Computer Science, or quantitative related field.

SOC Code: 15-2051

SOC Occupation Title: Data Scientists

Duration: Regular Hire

Work week: Full-time

Supervision Experience Required: No

Travel Required: None

Experience

5 years of expereince with data science. Requires skills and experience in the following:

• Expertise in applied statistics, exploratory data analysis, hypothesis testing, and probabilistic modeling.
• Proficiency in Python and R.
• Demonstrated experience building and deploying models using Amazon Web Services (AWS) tools.
• Demonstrated experience working with Data Build Tool (DBT).
• In-depth knowledge and experience with relational databases (SQL) and data warehouses.
• Demonstrated experience in querying, analyzing, and visualizing large datasets.
• Demonstrated experience in machine learning techniques.

Job duties

Performs safety analyses and develops and implements safety-related processes that support autonomous vehicle safety programs. Designs and deploys platforms that analyze safety evidence against internal standards, evaluate real-world crash data and driving behavior, and identify and assess safety anomalies and procedural risks. Supports regulatory safety-case submissions, including the local or state DMV permit renewal process, and enhances Safety Management System risk-management process, including the formal documentation and analysis of safety-related root causes. Develops and implements quantitative risk-management measures to identify, assess, prioritize, and mitigate safety risks associated with autonomous vehicle operations. Develops riskscoring and escalation process that evaluates safety anomalies based on severity, identifies root causes and consequences, tracks mitigation status, and determines whether an issue requires monitoring, mitigation, or further escalation. Develops a complexity-scoring engine that provides an early warning of increasingly complex safety procedures, enabling the team to proactively identify and address procedural risks before they result in an operational or safety incident.

Design and deploy safety-related data pipelines, models, tooling, and infrastructure in partnership with technical and non-technical stakeholders. Execute in-depth safety analyses on operational and simulation data, translating complex findings into actionable risk mitigation strategies. Implement safety initiatives in alignment with organizational safety objectives and industry best practices. Develop safety-related processes and reporting frameworks for organizational, operational, and product data to ensure accuracy, consistency, and reliability. Support the identification of systemic, latent, and emerging risks in fleet operations to advance root cause analyses and implement appropriate risk management measures. Define and enhance safety metrics by designing and validating novel measures using hypothesis testing and exploratory data analysis. Audit and validate technical safety evidence and artifacts across self-driving technologies, including hardware, software, and operations, to ensure alignment with quantitative safety arguments and applicable regulatory requirements through enterprise tool suites. Conduct root cause analyses of safety-related issues and support the development of data-driven corrective actions. Lead the quantitative development of internal and external safety reports, regulatory submissions, and public-facing communications, ensuring safety conclusions are statistically sound and well supported by evidence. Present and communicate the results of technical analyses to both technical and non-technical audiences. Develop and implement new processes and procedures related to safety metrics, data integrity, reporting, and issue management.