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Meteorologist and Data Scientist Developer

Job in College Park, Prince George's County, Maryland, 20741, USA
Listing for: Lynker
Full Time position
Listed on 2026-07-08
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 75000 - 100000 USD Yearly USD 75000.00 100000.00 YEAR
Job Description & How to Apply Below

Lynker is seeking a sharp Meteorologist and Data Scientist Developer. The selected individual will serve as a meteorologist/data scientist developer at the Weather Prediction Center (WPC) and will have direct interaction with scientists within NOAA as well as partners outside of NOAA, including NCEP centers, NWS weather forecast offices, NOAA research facilities, academia, and the NWS Science and Operations Officer community.

In this capacity the incumbent will work with these partners to develop and implement verification methods to gauge the effectiveness of new forecaster tools applied to operational and experimental forecasts, build the capacity to enhance impact decision support services (IDSS), and leverage machine learning techniques to enhance forecasting capabilities, including leading projects that apply advanced AI algorithms to predictive modeling.

In addition, the person selected will work to provide enhancements that build upon current forecaster tools, develop new services and forecaster tools, and transition promising work to operations. The incumbent will provide training materials on the enhanced forecaster products and tools, employ machine learning models to improve existing tools, and pioneer new data‑driven services.

Areas of particular need and interest include developing forecaster and verification tools for hazardous weather, using ensemble model output to aid forecaster generation of probabilistic products, integrating AI and machine learning workflows to optimize the processing of ensemble model output and other complex meteorological datasets, and applying neural networks to enhance high‑resolution numerical weather prediction models.

The ideal candidate will be able to identify pertinent datasets (satellite, land use, and meteorological), develop forecaster tools that may be implemented on web pages, and leverage AI‑driven data pipelines to automate the ingestion and preprocessing of vast meteorological datasets. Assignments are received in terms of expected outcomes, and incumbents act independently to develop methodologies and provide sound analyses and recommendations.

Projects may include analysis, application development, or other areas specific to the assignment.

Duties of the Meteorologist and Data Scientist Developer
  • Collaborate with meteorologists at NCEP, NWS field offices, academia, and outside partners to develop forecast tools for short to medium‑range time frames regarding hazardous weather.
  • Use scientific and technical meteorological expertise to develop tools for the determination of hazard information.
  • Contribute to formal scientific publications, attend off‑site conferences, symposia, and hazardous‑weather‑related outreach events as appropriate.
  • Collaborate to transition forecaster tools developed at WPC and elsewhere within NOAA into operations at WPC and other NOAA offices.
  • Develop web applications using modern industry languages and tools such as GIS, Python, and PHP.
  • Develop training materials to transition new tools and techniques into operations.
  • Perform related duties as assigned.
  • Design and train machine learning models to identify precursors to severe weather events.
  • Implement AI‑based anomaly detection systems to identify errors or gaps in real‑time forecast data.
Qualifications
  • Degree in meteorology, hydrology, or related science fields (BS required; MS or higher preferred).
  • Experience applying artificial intelligence (AI) and machine learning (ML) techniques to analyze and model complex environmental or meteorological datasets.
  • Experience with software development support in a team environment.
  • Experience with Python and Unix shell scripting within a UNIX/Linux environment.
  • Knowledge of deterministic and ensemble prediction system datasets and their application to hazardous weather diagnosis and prediction.
  • Knowledge of short‑to‑medium‑range weather forecasting.
  • Ability to organize, plan, and complete projects.
  • Excellent written and oral communication skills for documentation and presentations.
  • Ability to support team initiatives, demonstrate respect for team members, and seek team consensus.
Ideal Candidate Enhancements
  • Experience with development…
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