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Quantitative Weather Analyst Jobs (NOW HIRING)

Waymo

Staff Data Scientist, Weather

San Diego, CA

Demonstrated knowledge of data analysis libraries and packages in Python, R, and/or SQL. We prefer: * PhD in a quantitative, weather-adjacent field (Atmospheric Science, Meteorology, Hydrology, etc ...

Waymo

Staff Data Scientist, Weather

Mountain View, CA · On-site

$251K - $310K/yr

Demonstrated knowledge of data analysis libraries and packages in Python, R, and/or SQL. We prefer: * PhD in a quantitative, weather-adjacent field (Atmospheric Science, Meteorology, Hydrology, etc ...

PIMCO

Quantitative Research Analyst

Newport Beach, CA · On-site

$200 - $250/hr

... weather, oil, natural gas, metals or agricultural marketsStrong statistical and econometric ... quantitative concepts clearly and deliver accurate analysis in a time-sensitive front-office ...

PIMCO

Quantitative Research Analyst

Newport Beach, CA · On-site

... power, weather, oil, natural gas, metals or agricultural markets * Strong statistical and ... quantitative concepts clearly and deliver accurate analysis in a time-sensitive front-office ...

PIMCO

Quantitative Research Analyst

Newport Beach, CA · On-site

... power, weather, oil, natural gas, metals or agricultural markets * Strong statistical and ... quantitative concepts clearly and deliver accurate analysis in a time-sensitive front-office ...

NextEra Energy Resources

NY · On-site

$80 - $100/hr

Quantitative Finance Analyst Date: Jul 2, 2026 Company: NextEra Energy Requisition ID: 95661 ... weather products, and other financial or commercial assignments required to achieve group ...

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Quantitative Weather Analyst information

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$56.5K

$133.9K

$240K

How much do quantitative weather analyst jobs pay per year?

As of Sep 8, 2026, the average yearly pay for quantitative weather analyst in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What is a quantitative weather analyst?

A Quantitative Weather Analyst is a professional who uses mathematical models, statistical techniques, and computer-based tools to analyze and interpret weather data. They focus on producing accurate forecasts, assessing risks, and supporting decision-making in weather-sensitive industries such as finance, agriculture, and energy. Their work often involves large datasets, advanced programming skills, and collaboration with meteorologists to improve the precision of weather predictions.

What are the key skills and qualifications needed to thrive as a quantitative weather analyst?

To thrive as a Quantitative Weather Analyst, a strong background in meteorology, mathematics, statistics, and computer science—often supported by a relevant degree—is essential. Proficiency with numerical weather prediction models, data analysis software (like Python, R, or MATLAB), and experience with GIS or remote sensing tools are typically required. Analytical thinking, problem-solving skills, and effective communication further distinguish top performers in this role. Mastery of these areas is crucial for accurately interpreting complex weather data, developing reliable forecasts, and conveying insights to stakeholders.

How does a quantitative weather analyst typically collaborate with other teams within a meteorological organization?

Quantitative Weather Analysts often work closely with meteorologists, data scientists, and software engineers to develop and refine weather prediction models. They share their quantitative findings and statistical analyses to support operational forecasting and research initiatives. Regular collaboration ensures that data-driven insights are integrated into forecast products and that models are continuously improved based on feedback from both technical and non-technical team members. This cross-functional teamwork is essential for delivering accurate and actionable weather information.

What is the difference between Quantitative Weather Analyst vs Meteorologist?

AspectQuantitative Weather AnalystMeteorologist
Required CredentialsBachelor's in meteorology, atmospheric science, or related field; often certifications in data analysisBachelor's or higher in meteorology or atmospheric sciences; often licensed or certified as a broadcast meteorologist
Work EnvironmentData analysis firms, research institutions, government agencies; focus on data modelingBroadcast stations, news outlets, weather service agencies; focus on forecasting and communication
Employer & Industry UsagePrimarily in research, data analysis, and modeling roles within meteorology-related industriesIn media, government, and private forecasting sectors, providing weather forecasts and warnings

While both roles involve meteorology, Quantitative Weather Analysts focus on analyzing weather data and creating models, whereas Meteorologists primarily forecast weather and communicate findings to the public. The roles often overlap in skills and credentials but differ in their primary responsibilities and work environments.

What are popular job titles related to Quantitative Weather Analyst jobs?

For Quantitative Weather Analyst jobs, the most frequently searched job titles are:

Infographic showing various Quantitative Weather Analyst job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $133,877 per year, or $64.4 per hour.

Staff Data Scientist, Weather

San Diego, CA

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

Full-time

Re-posted 3 days ago

Job description

Rigorous evaluation of the Waymo Driver, including monitoring the performance of Waymo's fleet in the field, is a critical part of scaling our ride hailing service and achieving Waymo's ambitious goals. In this role, you will lead key initiatives for modeling weather patterns and their impact on Waymo's ride hailing service, and streamlining Waymo's operational procedures designed to mitigate weather-related challenges in real time and measuring the performance of the Waymo Driver in adverse weather conditions.

In this hybrid role you will report to the Data Science Lead for Driving Quality & Scope Expansion.

You will:

  • Define and uphold a high bar for measurement rigor. Ensure we can confidently rely on the evaluation signals informing deployment, scaling, and mitigation decisions. Identify and work to resolve any gaps where current evaluation signals are not scaling with Waymo's business or providing the necessary actionability for stakeholders.
  • Build pipelines and models integrating a range of existing and novel weather-specific data sources (1P/2P/3P) to enhance Waymo's weather intelligence and prediction capabilities.
  • 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. Communicate these findings to senior stakeholders.
  • Develop scalable and repeatable analysis frameworks that support multiple climate types, both domestically and internationally.
  • Optimize Waymo's operational processes for addressing adverse/extreme weather across a wide range of geographical territories, making them smarter, more responsive, and more efficient.
  • Develop a deep understanding of Waymo's long-term roadmap, and collaborate with leads in product, engineering, and systems engineering to unlock key deployment milestones. Be an opinionated partner influencing roadmaps for engineering work to improve our measurement capabilities.
  • Be an active technical contributor on the team, as well as a technical lead to junior data scientists. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods. Champion data science excellence and provide constructive technical feedback within the team and across Waymo.

You have:

  • Degree in a quantitative field (e.g. Statistics, Mathematics, Physics).
  • Either a PhD in a quantitative field and 8+ years of industry experience, or 12+ years of industry experience solving data science problems.
  • Experience working with and building models for spatio-temporal data.
  • Experience as a technical lead.
  • Experience working in highly cross-functional teams and championing data-driven culture.
  • Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models.
  • Demonstrated knowledge of data analysis libraries and packages in Python, R, and/or SQL. 

We prefer:

  • PhD in a quantitative, weather-adjacent field (Atmospheric Science, Meteorology, Hydrology, etc.), and/or academic experience developing and applying statistical methods in those fields.
  • Experience working with third-party (e.g., public / private) weather data sources and integrating multiple data sources.
  • Experience solving problems related to weather modeling or prediction.
  • A demonstrated track record of independently driving data science projects to deliver business value.
  • Experience with large-scale evaluation frameworks for software development.

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