Transit Data Science Fellow
U.S. Department of Transportation (DOT) ensures our Nation has the safest, most efficient and modern transportation system in the world, which improves the quality of life for all American people and communities, from rural to urban, and increases the productivity and competitiveness of American workers and businesses.
The Federal Transit Administration (FTA) Office of the Chief Data Officer (OCDO) is seeking a Transit Data Science Fellow to support high-impact analytics and research projects that inform how FTA delivers programs, evaluates performance, and supports transit agencies nationwide.
The OCDO leads FTA’s data strategy, culture, operations, and analytics. We transform how FTA uses data by:
- Applying advanced methods to generate insight and reduce burden (Analytics and Artificial Intelligence).
- Creating trusted, ready-to-use data (Data Management).
- Equipping staff to work independently with data (Data Culture).
- Making data accessible and meaningful (Data Transparency).
This Transit Data Science Fellow will participate on cross-functional analytics projects that explore how data science methods can improve federal transit operations and oversight. Projects may include:
- Performing exploratory data analysis across diverse FTA datasets.
- Building and evaluating statistical and machine learning models.
- Developing tools and visualizations to support internal decision-making.
- Identifying patterns, trends, and anomalies in operational data.
- Testing data quality and working with imperfect or incomplete data.
- Contributing to pilots that use natural language processing (NLP), geospatial methods, or automation to reduce manual workload.
- Presenting findings in clear, compelling formats for technical and non-technical audiences.
We’re looking for someone who:
- Can apply data science to real-world problems.
- Is comfortable with Python, R, SQL, or similar tools for analysis and modeling.
- Can translate messy datasets into usable insight and action.
- Communicates clearly across technical and non-technical audience.
This appointment is for one year. Extensions may be offered in increments of one year up to a total of five years. Extensions are contingent upon project needs and funding availability.
This opportunity offers a competitive stipend and travel allowance and is eligible for health insurance benefits.
This opportunity is located either on-site with the DOT FTA OCDO in Washington, DC, or remote from within the United States.
The participant will not enter into an employee/employer relationship with ORISE, ORAU, DOE, DOT, or any other office or agency. Instead, the participant will be affiliated with ORISE for the administration of the appointment through the ORISE letter of appointment and Terms of Appointment.
Qualifications
Applicants must have completed either a baccalaureate or master's degree in mathematics, statistics, computer science, data science, or other field directly related to this opportunity (for a complete list of these fields, please see Discipline(s) under Eligibility Requirements below) at the time of application. Master's-level applicants may also be currently pursuing the degree at the time of application.
An ideal candidate has proficiency with:
- Interpreting unique, complex data sets and applying statistical and analytic methods to discover patterns for guiding decision making, streamlining operations, or improving programs.
- Python, R, SQL or other analytical tools to develop analyses, reports, or data products.
- Refining business problems into objective, measurable problem statements and translating analyses into clear communications and visualizations to stakeholders.
A complete application consists of:
- Profile Information
- Application Questions (goals, experiences, and skills relevant to the opportunity)
- Transcript(s) - An unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. The selected candidate may be required to provide proof of completion of the degree before the appointment can start.
- A current resume/CV
- One Letter of recommendation - Applicants are required to provide contact information for one recommender in order to submit the application. The recommender will then be notified to submit the letter to Zintellect on behalf of the applicant. The letter of recommendation must be submitted before an offer is made.
If you have questions, please email USDOT@orau.org and list the reference code for this opportunity in the subject line of your email.
Point of Contact
Eligibility Requirements