Research Associate Statistician
Research Associate Statistician
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1 Vacancy
Job Description
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 hypothesisdriven statistical tests and implementing predictive modeling techniques. The successful candidate will structure and preprocess large complex datasetsincluding naturalistic driving data video and telematicsdevelop 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 nontechnical 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 daytoday project activities (e.g. literature reviews modeling research reporting and presentations) and disseminate research findings through technical reports conference presentations and peerreviewed 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 largescale structured and unstructured data Build and validate statistical and machine learning models Interpret results and draw datadriven 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 fastpaced 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 $80000; 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 handson transdisciplinary approach to preparing scholars to be leaders and problemsolvers. A comprehensive landgrant 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 36000 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.
Virginia Tech does not discriminate against employees students or applicants on the basis of age color disability sex (including pregnancy) gender gender identity gender expression genetic information ethnicity or national origin political affiliation race religion sexual orientation or military status or otherwise discriminate against employees or applicants who inquire about discuss or disclose their compensation or the compensation of other employees or applicants or on any other basis protected by law.
If you are an individual with a disability and desire an accommodation please contact Natalie Jett at during regular business hours at least 10 business days prior to the event.
Required Experience:
IC
Employment Type
Full Time
