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U.S. Department of Transportation (DOT)
Who we want to invite:
We are looking for a paid Fellow trained in data driven disciplines. This is a great opportunity to strengthen your programming and analysis skills with national data and to gain invaluable experience working with subject-matter experts. The ideal candidate will be experienced in data processing, programming, statistical analysis, and knowledgeable of data mining and predictive modeling. The fellowship offers an excellent opportunity to provide input, direction, and creativity into projects involving national databases as well as skill development and training, and networking opportunities. If this sounds exciting to you, come apply your data analysis and research skills to help shape the best U.S. transportation system!
How you will contribute:
You will be in the Office of Data Development and Standards (ODDS). The ODDS designs, develops and conducts data development programs to capture information on U.S. transportation system for effective use in decision making. ODDS staff work collaboratively across agencies, within and outside USDOT, to explore innovative methods of data collection/analysis/visualization and survey design in improving and initiating data development programs.
You will be involved with developing and implementing transportation data development programs through several projects. You will apply data analytics techniques to collect, augment, and analyze transportation data. You will be involved with researching administrative and auxiliary data sources to enhance the transportation data. Strong communication, coordination, and teamwork skills are essential to be successful in this role.
Stipend and Benefits:
- Stipend: $57,000 – $80,000 (Annual)
- Professional Development: $2,000
- Health Insurance: $3,000
- Relocation Expense: $2,000
The appointed Data Research Fellow must have received a Bachelor’s Degree, Master’s Degree or Ph.D. program in a data driven discipline required (e.g., Mathematics, Statistics, Data Science, Economics, Computer Science, Engineering, Social and Behavioral Science, Operation Research, Business Logistics, or Information Systems). Experience or knowledge in freight and supply chain issues desired.