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Extreme Weather Jobs (NOW HIRING)

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Health and Extreme Weather Research Position/Title/Fund: Health and Extreme Weather Research Deadline: Rolling basis until funds are exhausted Description: Extreme weather events--such as wildfires ...

Waymo

Staff Data Scientist, Weather

San Diego, CA · On-site

Measure the performance of the Waymo driver in adverse/extreme weather conditions (fog, rain, snow, ice, hail, flooding), providing input on Waymo's readiness to scale in challenging weather contexts.

Waymo

Staff Data Scientist, Weather

Mountain View, CA · On-site

$251K - $310K/yr

Measure the performance of the Waymo driver in adverse/extreme weather conditions (fog, rain, snow, ice, hail, flooding), providing input on Waymo's readiness to scale in challenging weather contexts.

Remedial Transportation Solutions

Operator

Shafter, CA · On-site

$28 - $35/hr

Expected to work in a variety of extreme weather conditions * Maintenance of licensing and certification on all vehicles the require licensing or certifications * Wear Safety PPE at all times

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How much do extreme weather jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for extreme weather in the United States is $26.47, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $29.57 per hour, depending on experience, location, and employer.

What is an extreme weather?

An Extreme Weather job involves working in environments affected by severe weather conditions, such as hurricanes, tornadoes, blizzards, or extreme heat. Professionals in this field include meteorologists, storm chasers, emergency responders, and disaster recovery specialists. Their responsibilities may include forecasting weather patterns, providing emergency aid, or assessing damage after a natural disaster. These jobs often require specialized training, physical endurance, and a willingness to work in hazardous conditions.

What are the key skills and qualifications needed to thrive in the extreme weather position, and why are they important?

To thrive in an Extreme Weather Specialist role, you need expertise in meteorology, atmospheric science, and data analysis, often supported by a relevant degree or certifications such as the Certified Broadcast Meteorologist (CBM) credential. Proficiency with advanced weather modeling software, radar systems, and geospatial analysis tools is essential for accurate forecasting and reporting. Strong communication, quick decision-making, and adaptability are essential soft skills to effectively convey urgent information and operate in high-pressure environments. These skills ensure timely and reliable information delivery, which is critical to public safety during severe weather events.

What are some common challenges faced by extreme weather specialists, and how are they typically addressed?

Extreme Weather Specialists often contend with high-pressure situations, rapidly evolving weather patterns, and the responsibility to deliver accurate, real-time updates to the public and stakeholders. These challenges are typically addressed through continuous training, teamwork with emergency management agencies, and the use of advanced forecasting technologies. Specialists must also be prepared to work irregular hours, including nights, weekends, or during active weather events, to ensure public safety. Effective communication and staying current with the latest research are key to meeting these demands and excelling in this dynamic field.

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extreme weather jobs near you
Infographic showing various Extreme Weather job openings in the United States as of September 2026, with employment types broken down into 79% Full Time, 18% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $55,057 per year, or $26.5 per hour.

Senior Data Scientist, Outage & Extreme Weather

Denver, CO • On-site

Technosylva
Software Development • 51 - 200 employees
Learn more about Technosylvaexternal

Full-time

Posted 3 days ago

New

Job description

About Technosylva
Technosylva is a global leader in wildfire and extreme weather risk mitigation software. The Company's market-leading solutions, enhanced by AI and machine learning capabilities, provide real-time and predictive insights to support electric utility, insurance and government agency customers.
Technosylva has provided critical solutions for the past 26 years. In 2022 the organization entered a period of significant growth and transformation with investment from TA Associates, a leading growth PE firm, scaling to about 175 employees and offering its product in over 10 countries. In 2024 General Atlantic, a leading global growth investor, announced a strategic growth investment in Technosylva to support the company in its mission.
Role Overview
We are seeking a Senior Data Scientist with deep expertise in modeling the impact of extreme weather on electric grid infrastructure, with a particular focus on transmission outage prediction. In this role, you will design, build, and operationalize machine learning and statistical models that predict weather-driven outages and failures across transmission and distribution systems, directly supporting utility decision-making before and during extreme weather events.
You will work at the intersection of atmospheric science, power systems, and machine learning-combining mechanistic, physics-based understanding of infrastructure failure with data-driven probabilistic methods. Your models will feed real-time operational products used by utilities to anticipate outages, position crews, and manage grid risk during storms, extreme winds, and wildfire conditions.
Responsibilities
  • Design, develop, and validate machine learning models to predict transmission outages driven by extreme weather, combining mechanistic and probabilistic approaches.
  • Build spatio-temporal models that link weather forecasts to infrastructure failure risk, including probability of failure (POF) estimates for transmission and distribution assets.
  • Develop models characterizing the interrelationship between transmission outages, extreme weather events, and wildfire ignition risk.
  • Integrate heterogeneous datasets-weather model output, asset and infrastructure data, historical outage records, and geospatial layers-into robust, reproducible modeling pipelines.
  • Operationalize research-grade models into fast, reliable production systems suitable for real-time forecasting workflows.
  • Evaluate and benchmark model performance against state-of-the-art methods and clearly communicate accuracy, skill, and uncertainty to internal teams and utility customers.
  • Collaborate with meteorologists, risk modelers, and software engineers to improve Technosylva's outage and extreme weather product capabilities.
  • Leverage agentic coding tools throughout the development lifecycle-using AI agents to accelerate model prototyping, pipeline development, testing, and documentation-while maintaining rigorous review and validation standards.

Requirements
Education
  • Ph.D. in Environmental Engineering, Atmospheric Science, Civil Engineering, Statistics, Data Science, or a related quantitative field strongly preferred.
  • A master's degree with substantial applied experience in weather-driven outage or infrastructure risk modeling will be considered.

Professional Experience
  • Demonstrated experience developing transmission outage prediction models-this is a core requirement for the role.
  • 5+ years of experience (academic or industry) applying statistical modeling and machine learning to grid reliability, storm outage prediction, or related energy-sector problems.
  • Experience working with utilities, ISOs/RTOs, or grid operators on weather-related operational forecasting is highly valued.
  • Track record of peer-reviewed publications, patents, or deployed production models in outage prediction, wildfire risk, or extreme weather impacts.

Modeling & Technical Skills
  • Strong grounding in machine learning methods (ensemble methods, neural networks, probabilistic models) and statistical modeling for spatio-temporal problems.
  • Experience combining physics-based/mechanistic models with data-driven approaches for infrastructure failure prediction.
  • Proficiency with geospatial data and tools (GeoPandas, ArcGIS or equivalent) and large multidimensional weather datasets.
  • Advanced Python skills (NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch) with the ability to write clean, well-documented, production-quality code; experience with R, SQL, or Julia is a plus.
  • Ability to optimize model runtime and computational workflows for real-time operational use.

Agentic Coding & AI-Assisted Development
  • Hands-on experience using agentic coding tools (Claude Code, Cursor, Copilot agents, or similar) as a core part of daily development workflows-not just autocomplete, but delegating multi-step coding tasks to AI agents.
  • Skilled at structuring work for AI agents: writing clear specifications, decomposing problems, and providing context so agents produce correct, maintainable code.
  • Strong judgment in reviewing and validating agent-generated code, especially for scientific correctness in modeling pipelines.

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