Quantitative Meteorologist (Atmospheric Science)

TL;DR

Quantitative Meteorologist (Atmospheric Science): Developing quantitative methods for identifying and scoring cloud-seeding opportunities with an accent on statistical analysis of meteorological data and operational decision-making. Focus on building reproducible analyses, automating forecasting workflows, and establishing defensible measures of precipitation-enhancement performance.

Location: On-site in El Segundo, CA. Relocation assistance provided.

Company

hirify.global is pioneering a modern cloud-seeding system to increase precipitation, improve water availability, and address severe-weather challenges.

What you will do

• Develop quantitative methods for identifying, scoring, and ranking cloud-seeding opportunities.
• Analyze historical and real-time meteorological data to understand conditions associated with successful precipitation outcomes.
• Design observational studies and statistical analyses to distinguish intervention effects from natural weather variability.
• Build tools for evaluating potential programs, including climatology, targetability, and sensitivity analysis.
• Collaborate with software engineers to automate meteorological forecasting and nowcasting workflows.
• Translate meteorological concepts into features, labels, and evaluation frameworks for machine-learning models.

Requirements

• Advanced degree in meteorology, atmospheric science, applied mathematics, statistics, physics, or a related quantitative field.
• Strong understanding of cloud and precipitation processes, mesoscale meteorology, and numerical weather prediction.
• Proficiency in Python and scientific computing tools including NumPy, SciPy, pandas, and xarray.
• Experience working with meteorological data formats such as GRIB, netCDF, radar, and satellite observations.
• Ability to formulate ambiguous scientific questions as measurable quantitative problems.
• Must be based in or able to relocate to El Segundo, CA for on-site work.

Nice to have

• PhD in meteorology or atmospheric science.
• Experience with WRF, HRRR, GFS, or ECMWF products and data assimilation.
• Knowledge of causal inference, Bayesian methods, spatial statistics, or decision science.
• Familiarity with radar meteorology, satellite retrievals, or atmospheric instrumentation.

Culture & Benefits

• Significant stock options with high potential upside as an early-stage company.
• 401(k) with employer matching.
• Full health coverage including medical, dental, and vision insurance.
• Unlimited PTO and paid parental leave for both parents.
• On-site perks including provided lunch and free EV charging at the HQ.