Data Scientist - DIRECT HIRE
Federal Transit AdministrationThis position is located in the Department of Transportation (DOT), Federal Transit Administration (FTA), Office of the Chief Data Officer (OCDO). OCDO develops strategic approaches to leveraging FTA's data assets, manages FTA's data governance, builds a strong data culture, manages data as a strategic asset, and uses data to improve mission delivery, operational efficiency, and actionable decision-making data, including via advanced analytic techniques and AI.As a Data Scientist, you will: Interact with analysts and internal customers to understand business processes, gatherrequirements, develop analysis methodologies, and coordinate development of data products. Perform analysis of a variety of data sources to provide data-driven insights and recommendations to the organization to streamline processes and improve program operations. Communicate analytical findings to technical and non-technical audiences, including senior leadership. Develop, document, and implement statistically reliable methods, strategies, and approaches to ensure valid and reliable information is provided to support management decision-making. Conduct tests to measure data quality and compliance with internal policy. Performs data wrangling and develop broadly applicable recommendations to deal with imperfections in data. Assist in building the foundation of scientific and technical capabilities within FTA to support ongoing and future data analytics projects. Educate others on technology, tools, and best practices. The ideal candidate will have demonstrated experience leveraging data to inform business process improvements and operational decision-making. The ideal candidate will contribute to project teams using outstanding analytical and problem-solving skills, performing sophisticated data analysis, and developing data visualizations.
Opens the company's application page
Listed via
USAJobs
usajobs.gov
Similar roles
Design & Tech
Related reads from TCHNX

Why AI Design Tools Are Quietly Replacing Junior Designers and What Actually Comes Next
AI tools promise efficiency, but London studios are discovering an unexpected paradox: automation creates new bottlenecks requiring precisely the expertise being eliminated. We investigate what's actually happening to entry-level design work.

The Inference Economy: Why AI’s Biggest Cost Shift Is Happening After Training
A major shift in AI economics is reshaping the industry. As training frontier models becomes more expensive and inference becomes dramatically cheaper, companies are being forced to rethink how they build, deploy, price, and monetise intelligent systems.

The Emergence of Small Language Models: Why Efficiency Is Overtaking Scale
As the AI industry confronts computational costs and environmental concerns, a new generation of compact models is proving that bigger isn't always better. Small language models are reshaping enterprise AI deployment.
