Meteorologist, Data Scientist

Lynker

. 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 .

Posted 9/21/2026full-timeRemote • Maryland • United StatesJuniorMid-Level💰 $75,000 - $120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing meteorological forecast tools using AI and machine learning techniques, with proficiency in Python and web application frameworks. Capable of collaborating effectively with diverse teams and communicating complex scientific concepts clearly.

Highest-signal resume keywords

Python ProgrammingMachine Learning TechniquesAI-Based Anomaly DetectionWeb Application DevelopmentMeteorological Data Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData Science FrameworksDeep Learning ApplicationsUnix Shell ScriptingGISNumerical Weather PredictionForecast Tool DevelopmentData Pipeline AutomationWeather Forecasting

Soft Skills

Excellent Communication SkillsProject OrganizationTeam CollaborationRespect for Team MembersConsensus Building

Tools & Technologies

TensorFlowPyTorchScikit-learnArcGISJavaScriptAPI Development

Industry Keywords

Atmospheric ScienceGeophysical SciencesHazardous WeatherShort to Medium Range ForecastingDeterministic Prediction Systems

Tech Stack

Tools & technologies

JavaScriptLinuxPHPPythonPyTorchScikit-LearnShell ScriptingTensorflowUnix

About the role

Key responsibilities & impact

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 determination of hazard information
Contribute to formal scientific publications and/or attend off-site conferences, symposia, and hazardous-weather-related outreach events
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
Design and train machine learning models to identify precursors to hazardous weather events
Implement AI-based anomaly detection systems to identify errors or gaps in real-time forecast data
Provide enhancements to current forecaster tools and develop new services and forecaster tools
Apply neural networks to enhance high-resolution numerical weather prediction models
Identify pertinent satellite, land use, and meteorological datasets and develop forecaster tools for web pages or forecaster platforms
Leverage AI-driven data pipelines to automate ingestion and preprocessing of vast meteorological datasets
Perform related duties as assigned

Requirements

What you’ll need

A degree (e.g. B.S. or B.A.) from an accredited institution in Atmospheric Science, Oceanography, or other Geophysical Sciences, Engineering, Computer Sciences, or Mathematics
At least 2 years of experience in related areas
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 data sets and their application to hazardous weather diagnosis and prediction
Knowledge of weather forecasting - short to medium range
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
Experience with development Frameworks for web based map applications (e.g. ArcGIS, JavaScript, API)
Proficiency in data science frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn
Experience with deep learning applications in weather prediction

Benefits

Comp & perks

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