Job Opportunities API

About the Company     At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.   A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.   Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight.    Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.    Meet the Team   As a Safety Statistician – Risk & Safety Analysis, you will play a critical role in how Torc evaluates, communicates, and makes decisions about the safety of its autonomous driving systems.   You will influence the design and execution of statistically rigorous analyses that inform safety assurance strategies, engineering priorities, and risk-based decision making. Your work will directly influence how safety performance and risk are measured, understood, and acted upon across the organization.   This is a technical role focused on applied statistics and decision support, not dashboarding, experimentation platforms, or generic ML product analytics.   What You’ll Do   Employ statistically sound analyses to answer high-impact safety and regulatory questions, including how system performance translates to risk   Apply statistical methods to quantify and assess risk using a variety of data sources including large-scale time-series data (e.g., vehicle and sensor data) and structured safety datasets   Bridge safety and engineering teams by translating complex analyses into information engineers can act on   Develop automated, production-ready analysis workflows that support continuous safety monitoring   Select and defend appropriate statistical approaches for sparse, noisy, or rare-event data, applying Bayesian and frequentist methods and leveraging machine learning techniques where appropriate   Communicate statistically defensible findings to technical leaders, safety stakeholders, and executives   What You’ll Need to Succeed   Advanced degree in Statistics or a closely related field   M.S. with 3+ years of experience, or   PhD with 1+ years of experience   Strong background in applied statistics, safety analysis, and risk estimation   Experience in autonomous vehicles, adjacent safety-critical domains (automotive, aerospace, defense, robotics, rail, etc.), or comparable actuarial experience   Experience working with complex, real-world datasets rather than clean or purely academic data   Hands-on experience using Python for analysis (SQL and/or R a plus, but not required)   Ability to communicate statistical concepts clearly to non-statistical audiences   Comfort operating independently as a technical leader in a cross-functional, distributed environment   Domain knowledge in Bayesian methods   Bonus Points   Experience applying Bayesian methods to estimate risk using disparate data sources (such as simulations and naturalistic driving)   Background applying statistics to engineering or physics-based systems   Familiarity with time-series analysis, uncertainty quantification, or rare-event modeling   Experience supporting executive or external stakeholder decision-making requiring quick turnarounds, balancing analytical rigor with timeliness   Per