Role Description 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. - 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. Qualifications - 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. Requirements - 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. Benefits - A competitive compensation package that includes a bonus component and stock options. - 100% paid medical, dental, and vision premiums for full-time employees. - 401K plan with a 6% employer match. - Flexibility in schedule and generous paid vacation (available immediately after start date). - Company-wide holiday office closures. - AD+D and Life Insurance.