Lynker is seeking a sharp Meteorologist and Data Scientist Developer. The individual selected 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. This includes: 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. The work will also strive to build the capacity to enhance impact decision support services (IDSS), effectively building a Weather Ready Nation. The role will also focus on leveraging machine learning techniques to enhance forecasting capabilities. This includes 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 as well as work to develop new services and forecaster tools. Promising work will be transitioned to operations. The incumbent will provide training materials on the enhanced forecaster products and tools. The individual will specifically employ machine learning models to improve existing tools and pioneer new, data-driven services.

Areas of particular need and interest to be addressed include developing forecaster and verification tools for hazardous weather. Additional areas of focus include the use of ensemble model output to aid forecaster generation of probabilistic products. A key focus will be integrating AI and machine learning workflows to optimize the processing of ensemble model output and other complex meteorological datasets. This also entails 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) and develop forecaster tools which may be implemented on web pages. Assignments are typically received in terms of expected outcomes, and incumbents are expected to act independently to develop methodologies, and to provide sound analyses and recommendations. Assigned projects may include analysis, application development, or other areas specific to the assignment. The ideal candidate will also leverage AI-driven data pipelines to automate the ingestion and preprocessing of vast meteorological datasets.

• 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.
• As appropriate, contribute to formal scientific publications, and/or attending 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.
• 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.

• Degree in meteorology, hydrology or related science fields (BS required, with MS or above 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 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, and experience with deep learning applications in weather prediction.

• 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