Physical Scientist - Seasonal Forecast System Developer

Lynker Corporation; College Park (MD); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Healthcare benefits

PTO and holidays

401(k) with company matching

ESOP

Job summary

Lynker Corporation is seeking a Seasonal Forecast System Developer to support the NOAA NCWCP in Riverdale Park, MD, focusing on marine components and AI/ML prediction models for global coupled seasonal forecasting.

The role offers a hybrid schedule: 2 days per week in-office at NCWCP/College Park and 3 days remote. The candidate will collaborate with OMD scientists and external partners to advance SFS and UFS infrastructure.

Qualifications

• Advanced knowledge of S2S prediction and coupled SFS development.
• Experience in ensemble-based forecasting and retrospective experiments.
• Proficiency in FORTRAN and Python.
• Experience with HPC and scripting.
• Familiarity with modern software development practices and version control.

Responsibilities

• Develop and evaluate global coupled ensemble forecasting systems.
• Work with OMD scientists and collaborators on SFS improvements.
• Design experiments including retrospectives and reforecasts.
• Explore initial and model uncertainties and probabilistic forecasts.
• Communicate results clearly in written and oral form.

Skills

S2S prediction

Ensemble forecasting

AI/ML for NWP

FORTRAN

Python

HPC

Git / GitHub

communication

teamwork

attention to detail

Education

Master's or PhD in atmospheric sciences or related physical science

Tools

Git

GitHub

Job description

Overview

Lynker is seeking a candidate to support the Office of Modeling and Development (OMD) of NWS in carrying out research and development work related forecast improvements for marine and seasonal forecasting. The candidate will be working on the physical model, Seasonal Forecast System (SFS) with a focus on the marine components, and development of OMD’s AI/ML prediction models for global coupled seasonal and marine forecasting. SFS is the Unified Forecast System’s (UFS) global-coupled seasonal forecasting application, which will replace CFSv2. The work location is at the NOAA Center for Weather and Climate Prediction (NCWCP) in Riverdale Park, MD.

The Ideal Physical Scientist and Seasonal Forecast System Developer will be able to work a hybrid schedule, working 2 days per week from the NOAA Center for Weather and Climate Prediction (NCWCP) office in College Park, MD, and the remaining 3 days per week from home.

Responsibilities

Duties of the Seasonal Forecast System Developer will include the following:

The candidate will perform job duties in a high-quality, independent, and collaborative way, developing and applying innovative methods for the primary work areas. The candidate will work with OMD scientists and external collaborators to develop and evaluate the current and future operational seasonal and marine forecasting systems. The candidate will work with the UFS infrastructure in designing and evaluating the global coupled ensemble forecasting systems for long range forecasting. Detailed responsibilities will include at least two aspects or more of the following areas.

• Development of global coupled Numerical Weather Prediction (NWP) models.
• Development of marine (ocean and sea ice) forecast systems.
• Development of subseasonal to seasonal probabilistic forecasting systems.
• Development of AI/ML techniques for seasonal and marine forecasting systems.
• Designing and conducting retrospective ensemble experiments and re-forecasts.
• Exploring initial or analysis uncertainties, and/or model uncertainties (or model stochastic perturbations).
• Analysis and evaluation of S2S probabilistic forecasts, and applications of multi-model ensembles and statistical post processing.

Qualifications

The Seasonal Forecast System Developer selected should have the following:

A Master or PhD’s Degree or equivalence in atmospheric sciences or meteorology, oceanic, mathematics, or related physical science with 1-2 years of experience in the area of global coupled ensemble forecast system development, sub-seasonal to seasonal prediction, numerical prediction, and/or AI/ML foundational prediction models. Candidates must be a U.S. Citizen or Permanent Resident Card Holder to qualify (please indicate in your cover letter).

Demonstrated knowledge, skills, and abilities in the following areas:

• Advanced knowledge of S2S prediction and experience in developing ensemble based and coupled SFS for research and operational implementation.
• Development of AI-ML methods for NWP and/or geophysical applications.
• Excellent knowledge and skills of modern programming languages and object-oriented languages, such as FORTRAN and Python.
• Skills and knowledge of the High Performance Computing (HPC) environment with strong scripting capabilities.
• Proficient with modern software development practices and version control software (e.g., Git and GitHub).
• Demonstrated skill in communicating effectively with scientists of diverse backgrounds on technical details of the work plan and present results accurately and clearly in both oral and written form.
• Ability to work independently on complex problems in a team and fast-paced environment and demonstrated skill in performing tasks requiring organization and attention to detail.
• Ability to support team initiatives, demonstrate respect for team members, and seek team consensus.

The Ideal Seasonal Forecast System Developer will have the following:

• Deep knowledge of ensemble strategy, reanalysis/reforecasting, and IC uncertainty.
• Familiarity with operational NWP and/or an operational forecasting environment and experience with advanced technical workflows.
• Experience with UFS applications and UFS infrastructure and knowledge of earth system modeling.
• Familiarity with agile software development practices.

About Lynker

Lynker is a growing, employee owned 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 professionals who embrace sound science and creative solutions. Lynker’s benefits include the following:

• Comprehensive healthcare for the employee at no monthly cost
• Healthcare benefit covers medical, prescription drug, dental, and vision
• Personal Time Off (PTO) Policy plus paid holidays
• Highly competitive compensation plan regularly calibrated against industry and location benchmarks
• 401(k) retirement plan with company-matching
• Employee Stock Ownership Plan (ESOP) - we're all company owners!
• Flexible spending accounts
• Employee assistance program (EAP)
• Short- and long-term disability insurance
• Life and accident insurance
• Tuition assistance/Training/Workforce improvement reimbursement per year
• Spot bonuses for exceptional performance
• Annual Employee Recognition Awards with bonuses
• Employee Referral Program
• Free centralized, self-directed Learning Management System to learn at your own pace
• Personalized career growth plans for every employee

Lynker is an E-Verify employer.

Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.