AI-Driven Meteorologist & Data Scientist

Lynker; College Park, Northern (MD, KY); Hybrid; USD 95,000 - 130,000; Full time

Benefits offered by this job

Healthcare coverage

PTO and holidays

401(k) with company match

ESOP

Learning management system

Spot bonuses

Job summary

Lynker seeks a Meteorologist and Data Scientist Developer to support a long-term contract with the Weather Prediction Center. The role involves collaborating with NOAA scientists and external partners to advance forecast tools and AI-enabled services.

The ideal candidate will apply machine learning to hazard forecasting, develop web-based tools using Python, GIS, and PHP, and help transition innovations into operations while providing training materials for end users.

Qualifications

• Degree in Atmospheric Science, Oceanography, Geophysical Sciences, Engineering, CS, or Mathematics.
• Experience applying AI/ML to environmental or meteorological datasets.
• Experience with Python and UNIX/Linux scripting.
• Knowledge of deterministic and ensemble prediction datasets for hazardous weather.
• Strong communication and teamwork skills.

Responsibilities

• Collaborate with NCEP/NWS/NOAA partners to develop forecast tools for hazardous weather.
• Develop tools for hazard information and web applications using GIS, Python, and PHP.
• Design and train machine learning models to identify precursors to hazardous weather events.
• Implement AI-based anomaly detection systems for real-time forecast data.
• Transition forecaster tools to operations within NOAA and WPC.
• Create training materials to enable deployment of new tools.

Skills

AI/ML techniques

Python

Unix shell scripting

Weather forecasting

Data analysis

Team collaboration

Education

B.S. in Atmospheric Science or related field

Tools

TensorFlow

PyTorch

Scikit-learn

ArcGIS

JavaScript

API development

UNIX/Linux

Job description

Lynker seeks a Meteorologist and Data Scientist Developer to support a long-term contract with the Weather Prediction Center. The role involves collaborating with NOAA scientists and external partners to advance forecast tools and AI-enabled services.

The ideal candidate will apply machine learning to hazard forecasting, develop web-based tools using Python, GIS, and PHP, and help transition innovations into operations while providing training materials for end users.