Technical Staff, Transportation Data Analytics and Decision Sciences

Requisition Id 13073 

 

Overview:

Oak Ridge National Laboratory (ORNL) is a U.S. Department of Energy (DOE) Office of Science national laboratory, with an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,200 people! ORNL’s decadal vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL’s broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation. Come join us as we solve the nation's biggest challenges!

 

Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. Our diverse capabilities span a broad range of scientific and engineering disciplines, enabling the Laboratory to explore fundamental science challenges and to carry out the research needed to accelerate the delivery of solutions to the marketplace. We are seeking a professional to fill a Technical Research Support position in the Transportation Analytics and Decision Sciences group within the Buildings and Transportation Sciences Division (BTSD), Energy Science and Technology Directorate (ESTD) at ORNL. The team consists of researchers, technical professionals, and software developers focused on conducting research in world-class facilities and deploying science-based knowledge in real-world deployment applications. The work supports the U.S. DOE Vehicle Technologies Office and the U.S. DOT Federal Highway Administration by developing/supporting public-facing transportation and energy analysis tools combining and analyzing large datasets and reporting analytical results. This position requires working with sponsors to develop and deploy solutions and technologies. Candidate selection will be based on qualifications, relevant experience, skills, and education.  

 

Major Duties / Responsibilities:

If selected, you will provide expert data mining and analysis to identify patterns and draw conclusions from data on freight and passenger transportation projects to solve complex technical problems. Major responsibilities include:  

• Research, develop, and test transportation data analysis tools involving database mining and reporting results in a variety of mediums.

• Author novel computer code, in a common computer language (e.g., Python and R) to streamline the data collection process from over 50 sources and complete post-processing analysis and serving of results through website tools and visualization. 
• Review transportation data inputs and results and provide analysis to a multi-functional team. 
• Test, debug/troubleshoot, and maintain specialized software programs and applications with a continuous integration process.  
• Author/Co-author technical reports, user guides, and/or manuals related to transportation data analytics. 
• Present and report research results and publish scientific findings at industry conferences and in peer-reviewed journals. 
• Deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace - in how we treat one another, work together, and measure success.

 

Basic Qualifications:  

You will have earned a PhD in Civil Engineering, Mechanical Engineering, Computer Science, or a related field, and completed one year of field experience. Other minimum qualifications include:    

• Fluency in at least (1) common computer language and version control software. 
• Demonstrable knowledge of transportation and logistics. 

• Previous experience with large datasets, including data mining and analysis.
• Excellent communications skills for visualization and presentation of methodology, results, and demonstrations.  
• Demonstrable success in team-based environments and ability to independently identify and solve challenging technical problems.  
• Demonstrable commitment to ethical and professional values as well as maintain a compliance with environmental, safety, health, and quality standards.  

 

Preferred Qualifications:  

You may have some of the following preferred qualifications, though none are required: 

• Extensive experience and fluency in Python and R computer languages. 
• Background in statistics and data analytics.