Global Models Post-Processing Scientific Support Specialist in College Park, Maryland at Lynker Technologies

Lynker Technologies
Global Models Post-Processing Scientific Support Specialist

US-MD-College Park

Job ID: 2026-1563
Type: Full-Time
# of Openings: 1
Category: Physical Scientist
College Park, MD

Overview

Lynker Corporation, a Federal Government Contractor, is seeking to fill a full-time position supporting the National Centers for Environmental Prediction (NCEP) at the Environmental Modeling Center (EMC). The Global Models Post-Processing Scientific Support Specialist serves as a member of the Post-Processing team within the Verification, Post-Processing, and Product Generation Branch (VPPPGB) in a fast-paced, highly collaborative environment. The incumbent will develop, maintain, and support atmospheric post-processed products from EMC’s suite of global scale Earth System Models (ESMs), such as the Global Forecast System (GFS) and the Global Ensemble Forecast System (GEFS), with a particular focus on transitioning to a next generation calibrated suite of model-integrated and post-processed guidance in support of the National Weather Service (NWS) probabilistic Impact-Based Decision Support Services (IDSS) roadmap. The incumbent will be expected to communicate scientific results via both oral presentation briefings and written reports to internal and external customers, and will have direct interaction with NOAA scientists, NCEP centers, NWS forecast offices, and academic partners. This role is contingent on contract modification.

More information about VPPPGB can be found at: https://www.emc.ncep.noaa.gov/emc/pages/vpppgb-description.php

Responsibilities

The Global Models Post-Processing Scientific Support Specialist will have the following Duties:

• Provide general support for post-processing and atmospheric product generation of global scale ESMs, such as the GFS and GEFS, using the Unified Post Processor (UPP) software framework, including creating new products and maintaining legacy data products.
• Develop software for global models post processing and products following guidelines and ideas from the NWS probabilistic IDSS roadmap.
• Interact with NWS/NCEP/EMC and external partner domain scientists and engineers.

• Adhere to DOC/NOAA/NWS Information Technology policies and procedures.
• Adhere to project-specific software development guidelines and practices.
• Complete scientific projects in a timely fashion according to internal and external schedules.
• Actively contribute to review of scientific ideas at status/technical meetings.
• Contribute to a monthly task status report.
• Report regularly to senior project managers on project task completion status.

Qualifications

The Global Models Post-Processing Scientific Support Specialist selected should have the following:

• At least an Masters or equivalent experience in atmospheric sciences or meteorology, mathematics, or a related physical science.
• Strong experience working with model output from both deterministic and ensemble based scale global ESMs.
• Strong experience working in a high-performance supercomputer UNIX environment with advanced scripting languages such as Python and the korn shell.
• Strong knowledge of computing languages such as Fortran, C, and C++.
• Ability to visualize model output using Python scripting and libraries, GEMPAK, or other visualization software.
• Demonstrated knowledge with using GitHub to manage software repositories and projects.
• Demonstrated skill in communicating effectively with scientists of diverse backgrounds, and the ability to present results accurately and clearly in both oral and written form.
• Knowledge of common meteorological data formats, such as BUFR, NetCDF, HDF, and GRIB, etc.
• Some knowledge of using web page technology and languages (HTML, Javascript, CSS, etc.) to display model output data.
• Ability to work independently and in a team environment on complex problems.
• Demonstrated skill in performing tasks requiring organization and attention to detail.

The Ideal Global Models Post-Processing Scientific Support Specialist will also have the following:

• Familiarity with environmental datasets, including observations and ensemble-based model output.
• Ability to work in a fast-paced environment.
• Demonstrated skill in performing tasks requiring organization and attention to detail.
• Knowledge of statistical principles and strong analytical skills.
• Desire to explore and apply Artificial Intelligence/Machine Learning techniques to model product output on global model timescales.

• A passion for the National Weather Service mission.

• Ability to accept assigned tasking, but also engage as a creative self-starter.
• Ability to work both independently and collaboratively.
• Driven by curiosity and willing to try new techniques and learn new skills.
• Ability to remain flexible as projects and tasks evolve.

About Lynker

Lynker is a growing, employee owned, small business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.

We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities – creatively and effectively.

Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled and diverse professionals who embrace sound science and creative solutions. Lynker's benefits include the following:

• Personalized career growth plans for every employee

Lynker is an E-Verify employer.

Lynker is proud to be an Equal Opportunity Employer and encourages women, minorities, individuals with disabilities and veterans to apply.