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Seasonal Weather Forecasting Jobs (NOW HIRING)

Saic

Scientific AI Programmer

Princeton, NJ · On-site

$60 - $80/hr

Through the work of this position, SAIC will develop a seasonal to subseason (S2S) AI weather forecast model.The Scientific AI programmer will evaluate an existing emulator and develop a prototype ...

SAIC

Scientific AI Programmer

Princeton, NJ · On-site +1

$40K - $80K/yr

Through the work of this position, SAIC will develop a seasonal to subseason (S2S) AI weather forecast model. The Scientific AI programmer will evaluate an existing emulator and develop a prototype ...

SAIC

Scientific AI Programmer

Princeton, NJ · On-site

$40K - $80K/yr

Through the work of this position, SAIC will develop a seasonal to subseason (S2S) AI weather forecast model. The Scientific AI programmer will evaluate an existing emulator and develop a prototype ...

Tailored Management

LCK Airport Ground Agent

Columbus, OH · On-site

$16 - $17/hr

Temperature variable environmental conditions based on the daily weather forecast. May be exposed to seasonal temperatures and precipitation, dust etc. Noise subject to aircraft engine and equipment ...

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Seasonal Weather Forecasting information

What is seasonal weather forecasting?

Seasonal weather forecasting is the process of predicting average weather conditions—such as temperature and rainfall—over a period of several weeks to several months, typically up to a season ahead. Unlike short-term forecasts that predict specific daily weather, seasonal forecasts provide general trends and probabilities for broader timeframes. These forecasts use climate models, historical data, and current atmospheric and oceanic conditions (like El Niño or La Niña) to make predictions. Seasonal forecasts are valuable for agriculture, energy planning, water resource management, and disaster preparedness.

What are the key skills and qualifications needed to thrive as a seasonal weather forecaster?

To thrive as a Seasonal Weather Forecaster, you need strong expertise in meteorology, climate science, and data analysis, often supported by a degree in atmospheric sciences or a related field. Familiarity with forecasting models, statistical analysis software, and Geographic Information Systems (GIS) is typically required. Excellent problem-solving, communication, and teamwork skills help convey complex forecasts to diverse audiences and collaborate with stakeholders. These combined abilities ensure accurate, actionable seasonal forecasts that support decision-making in weather-sensitive sectors.

What are some common challenges faced in a seasonal weather forecasting role, and how can they be managed?

Professionals in seasonal weather forecasting often encounter challenges such as limited historical data, high model uncertainty, and rapidly changing climate patterns. Managing these challenges involves leveraging advanced statistical models, continuously updating data inputs, and collaborating closely with climatologists and data scientists. It's important to communicate forecast uncertainty clearly to stakeholders and stay current with the latest research and technological advancements in the field. Teamwork and ongoing professional development are key to overcoming these obstacles and delivering accurate, actionable forecasts.

What is the difference between Seasonal Weather Forecasting vs Meteorologist?

AspectSeasonal Weather ForecastingMeteorologist
CredentialsDegree in meteorology or atmospheric sciences, certifications varyDegree in meteorology, atmospheric sciences, or related field; often includes certifications
Work EnvironmentResearch centers, government agencies, climate organizationsTV stations, radio, government agencies, private firms
Industry UsageFocuses on long-term seasonal predictionsProvides daily weather updates, forecasts, and analysis
Search & Comparison IntentUnderstanding seasonal climate patternsDaily weather forecasts and analysis

Seasonal Weather Forecasting specializes in predicting climate trends over months, aiding agriculture and planning. Meteorologists provide daily weather updates and short-term forecasts. While both roles require meteorological knowledge, seasonal forecasting emphasizes long-term climate patterns, whereas meteorologists focus on immediate weather conditions.

Do weather forecasters make good money?

Weather forecasters, including those specializing in seasonal weather forecasting, typically earn a median annual salary that varies by experience and location, with many earning between $40,000 and $100,000. Advanced roles or those with specialized skills in meteorology and forecasting tools can lead to higher salaries, especially in broadcast or government agencies.

How do I become a seasonal weather forecaster?

To become a seasonal weather forecaster, typically a bachelor's degree in meteorology, atmospheric science, or a related field is required. Gaining experience through internships, developing skills in weather modeling software, and obtaining certifications such as the Certified Broadcast Meteorologist (CBM) can improve job prospects. Strong analytical skills and the ability to interpret complex data are essential in this role.

What cities are hiring for Seasonal Weather Forecasting jobs?

Cities with the most Seasonal Weather Forecasting job openings:

What are the most commonly searched types of Weather Forecasting jobs?

The most popular types of Weather Forecasting jobs are:

What states have the most Seasonal Weather Forecasting jobs?

States with the most job openings for Seasonal Weather Forecasting jobs include:

What are popular job titles related to Seasonal Weather Forecasting jobs?

For Seasonal Weather Forecasting jobs, the most frequently searched job titles are:

Seasonal Weather Forecasting jobs near you

Scientific AI Programmer

Princeton, NJ • On-site

Saic
IT Services • 10K+ employees
Learn more about Saicexternal

$60 - $80/hr

Other

Re-posted 11 days ago

SAIC rating

7.6

Company rating: 7.6 out of 10

Based on 81 frontline employees who took The Breakroom Quiz

103rd of 226 rated it services

Job description

Description

SAIC is seeking an experienced Scientific AI programmer for a position at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) that will focus on creating a complex earth system model emulator. Through the work of this position, SAIC will develop a seasonal to subseason (S2S) AI weather forecast model.The Scientific AI programmer will evaluate an existing emulator and develop a prototype for the S2S timescale.You will work collaboratively with federal, contractor, university, and private sector scientists and developers and with the scientific evaluation team to assess the readiness of the AI forecast model for operational use.

This position requires an ability to obtain and maintain a Public Trust background investigation. This position is located in Princeton, NJ.

Responsibilities include, but are limited to:

  • Evaluate the existing seasonal to decadal AI emulator prototype to determine its utility for S2S timescales
  • Build an S2S AI emulator using SPEAR hindcasts, reanalysis, and other earth-system data for S2S forecasts
  • Determine the operational readiness of the S2S AI emulator
  • Coordinate with federal, contractor, university, and private sector scientists to align variables and training frameworks with research objectives
  • Deliver status updates through various communication channels such as team meetings and written reports

Qualifications

Required Education:

  • Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience

Required Qualifications:

  • A Bachelor’s degree in Computer Science, Information Systems, Engineering, Business or other related scientific or technical discipline.
  • Two years of experience in developing and training AI models using large data sets
  • Four years of specialized experience in determining information technology effects on the organizational structure and determining the ability that IT can support/meet organizational goals.
  • With a Master’s Degree (in the fields described in Min. Education above): two years experience
  • With a PH.D. (in the fields described in Min. Education above).: no experience required
  • With at least 8 years of specialized experience, a degree is not required.
  • Proficient in Python Programming
  • Experience managing projects with Git
  • Strong interpersonal skills to support collaborative team environments

Desirable Skills:

  • Basic knowledge of ocean, atmosphere and/or climate and weather processes or a related science.
  • Experience with object storage and traditional disk environments
  • Experience using NetCDF and Zarr datasets
  • Familiarity with High-Performance Computing (HPC) environments and batch queuing systems like Slurm.
  • Experience with modern AI-assisted coding workflows and/or MLOps tools to accelerate development cycles.

Background:

The Allen Institute for Artificial Intelligence (Ai2) and Multiscale Machine Learning In Coupled Earth System Modeling project (M²LInES), in partnership with GFDL, are developing several AI emulators for long time-scale simulations.These include an atmosphere model (ACE), an ocean model (Samudra), and a coupled model emulator (SamudrACE).The Software Engineering for Novel Architectures (SENA) initiative funded GFDL in FY2026 to develop an AI model emulator at seasonal to decadal timescales using data from GFDL’s SPEAR mode.The SPEAR emulator project began in January 2026.

Program and Project Details:

The proposed work is a continuation of the previous research of SamudraACE and the SPEAR emulator to apply these methods to the subseasonal to seasonal (S2S) timescales.The work will be done primarily on NOAA systems.When ready, the S2S AI forecast will be transitioned into the NOAA EAGLE Project pipeline for operational use.

Target salary range: $40,001 - $80,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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