Statistician

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:

The Safety Data Analysis Team within Torc’s Safety and Regulatory Department is responsible for providing the company with internal, but independent, oversight related to safety. The team includes accomplished experts in the areas of safety standards, safety management, and large-scale safety data analyses. This team collaborates across all areas of Torc, including product engineering, product safety & release, fleet operations, autonomy, simulation, and others to both foster a positive safety culture and identify solutions to controlling risk. As part of this team, you will be identifying solutions that build safety and trustworthiness into commercially successful automated driving systems.

What you will do:

• The Statistician, within the Safety Data Analysis Team will be using their statistical expertise to translate discussion from a variety of stakeholders into core questions and then robust designs that answer those questions. You will be answering safety assurance related questions relevant to transportation and autonomous driving systems.

• Being a software and automated vehicle company, this role involves working with large-scale, heterogenous data that are generated by sensors in software testing and during on-road operations. Your day-to-day work will leverage Python and its scientific libraries as well as R. A large portion of this work will require integration of physics and engineering principles to prepare data and evaluate its accuracy. You will also be connecting analyses with development workflows to automate the safety related monitoring of the organization and development process.

• Anticipate, research, and maintain facility with statistical methods used in ground transportation safety domain as well as analog domains

• Identify and select appropriate analyses methods for data ranging in scale from dense to sparse; apply statistical principals to manage bias and select appropriate sampling strategies; develop models and compare using statistical performance …