Principal Data Scientist

ARA Career•Atlantic City International Airport, NJ

1d•Onsite

About The Position

ARA is seeking experienced data scientists to work full-time for our Transportation Division Aviation Directorate. This is a full-time position on-site at the Federal Aviation Administration (FAA) William J. Hughes Technical Center (WJHTC) for Advanced Aerospace, co-located at the Atlantic City International Airport. This position will support a matrix team of talented personnel to conduct research development and test and evaluation of the safe integration of emerging operations, such as Advanced Air Mobility (AAM), into the United States National Airspace System (NAS). This work will be accomplished using the unique laboratory capabilities and tools resident at the FAA WJHTC. The team has been tasked to lead human-in-the-loop (HITL) simulations to inform initial entry into service at select major metropolitan areas and the team is researching future states for AAM operations as described in the FAA’s Urban Air Mobility Concept of Operations. The team intends to use AI, rule-based algorithms, and large language modeling to create software with the capability to evaluate vertiport placements and potential airspace usage (routes, corridors). ARA’s data scientists will enable pre-evaluation of potential vertiport sites and proposed routes to support suitability decisions earlier in an agile, swift M&S process for this applied research. Also, more routes and sites will be evaluated faster as precursor to the HITL simulations, saving both time and money.

Requirements

BS in a STEM discipline from an accredited college or university.
15+ years of relevant experience in data science or machine learning model development and validations.
Advanced degree may be considered in partial fulfillment of the experience requirement if directly applicable.
Must meet suitability requirements to work for a U.S. government agency.

Nice To Haves

Experience in aviation operations, engineering, and/or human factors preferred.

Responsibilities

Support software development of AI rule-based algorithms and large language modeling with the capability to evaluate vertiport placements and potential airspace usage (routes, corridors).
Participate in agile planning discussions including sprint planning (what to deliver), daily stand-ups/“scrums” (progress/blockers), reviews (feedback), and retrospectives. These meetings, often using story points for estimation, ensure a sustainable, realistic pace.
Design and implement data ingestion, cleaning, and structuring workflows to support repeatable analysis of simulation outputs.
Develop machine learning models to generalize and extrapolate findings from one simulated airport or vertiport environment to comparable operational environments.
Conduct predictive analytics and sensitivity analyses to assess throughput, safety margins, infrastructure impacts, and operational tradeoffs.
Support the building of automated analytics pipelines and scenario comparison tools to support rapid iteration across airport configurations and traffic assumptions.
Provide and ensure model transparency, traceability, and explainability to support engineering validation.
Develop data visualizations and decision-support products that translate complex simulation results into actionable insights for scientists, engineers, researchers, and leadership.
Support integration of AI-enabled analytics with existing FAA simulation environments and research workflows.