Research Associate, Statistician

Job Description

The Research Associate/Statistician, in conjunction with principal investigators, will lead the analysis, documentation, and interpretation of research results across all studies in the Division of Data Analytics. The candidate will also support analysis efforts across other research divisions within VTTI. This role will involve both traditional statistical analysis and the development of advanced machine learning models to address a broad range of transportation issues, including but not limited to traffic safety, automated driving system, advanced driver assistant systems, and human factor.

Analysis tasks will include identifying relevant driving risk factors, designing sampling strategies, performing hypothesis-driven statistical tests, and implementing predictive modeling techniques. The successful candidate will structure and preprocess large, complex datasets—including naturalistic driving data, video, and telematics—develop code for data analysis, and contribute to reproducible research pipelines. Responsibilities also include interpreting model results, evaluating performance metrics, and communicating findings effectively to both technical and non-technical audiences.

The successful applicant will perform work involving conventional statistical analysis as well as modern machine learning approaches, with applications to human factors and transportation safety. This includes managing projects with complex data structures, proposing and implementing novel modeling techniques, and contributing to the development of transformative transportation technologies. The employee is expected to support proposal development, oversee day-to-day project activities (e.g., literature reviews, modeling, research execution, reporting, and presentations), and disseminate research findings through technical reports, conference presentations, and peer-reviewed publications. Some travel may be required to conduct research or present results.

Duties and responsibilities:
Independently lead and contribute to research proposals | Conduct literature reviews with minimal supervision | Develop work plans, protocols, and analysis procedures | Review and refine research plans, models, and reports | Collaborate with subcontractors and interface with sponsors | Collect, clean, and analyze large-scale structured and unstructured data | Build and validate statistical and machine learning models | Interpret results and draw data-driven conclusions | Write technical reports and contribute to publications | Present findings to internal and external audiences | Manage project tasks and timelines independently | Travel as needed

Required Qualifications

• Advanced Degree in Computer Engineering, Computer Science, or a related technical field.
• Work experience and/or experience in statistical or epidemiological research.
• Proficiency with multivariate, longitudinal, and categorical data analyses and modeling.
• Competency with a statistical computing package such as SAS, R, and Python and experience/interest in working with large longitudinal data sets.
• Knowledge on advanced machine learning and language models.
• Computing capabilities should include the ability to structure and filter large transportation data sets and integrating relational databases with analysis software.
• Thorough understanding of experimental design and methods.
• Proficiency with descriptive and inferential statistical analysis techniques.
• Excellent communication skills.
• Strong organizational skills.
• Willingness to work in a fast-paced flexible research environment.
• Ability to work independently on statistics related topics with minimum supervision

Preferred Qualifications

• Proficiency with data collection and working knowledge of analysis software packages.
• Experience in transportation or related field.
• Proficiency with database languages including SQL.

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Restricted

Salary Information

Starting rate of $80,000; commensurate with experience

Hours per week

40

Review Date

4/21/2025

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.