Como Quantitative Meteorologist en Rainmaker, serás el puente entre la ciencia atmosférica, el análisis estadístico y las operaciones. Desarrollarás métodos rigurosos para identificar oportunidades de siembra de nubes, evaluar operaciones completadas y mejorar los flujos de pronóstico. Construirás herramientas reutilizables y análisis cuantitativos para apoyar decisiones operativas y el diseño de programas comerciales, colaborando estrechamente con ingenieros de software y ML.

Responsibilities

Develop quantitative methods for identifying, scoring, and ranking cloud-seeding opportunities.
Analyze historical and real-time meteorological data to understand the atmospheric and operational conditions associated with successful targeting and precipitation outcomes.
Design observational studies, experiments, and statistical analyses that distinguish intervention effects from natural weather variability as rigorously as the available data permits.
Establish honest uncertainty bounds and communicate when the evidence does not support a causal conclusion.
Build reusable tools for evaluating potential cloud-seeding programs, including climatology, seedable-hour frequency, targetability, operating constraints, expected opportunity, program design, and sensitivity analysis.
Work with software engineers to automate meteorological forecasting and nowcasting workflows used by flight and field operations.
Develop decision-support methods that combine NWP, ensembles, radar, satellite, sounding, aircraft, UAS, surface, and in-situ observations.
Define ground truth, baselines, validation methods, and performance metrics for forecasting, retrieval, precipitation-estimation, and intervention-analysis systems.
Translate meteorological concepts into features, labels, physical constraints, evaluation frameworks, and failure cases for machine-learning work.
Work with ML and software engineers on hybrid physical, statistical, and learning-based approaches while retaining responsibility for meteorological validity.
Produce technical analyses that support customer proposals, program design, business development, scientific validation, and operational reviews.
Create stronger feedback loops between forecasting, field operations, sensor development, research, and model development.
Communicate results clearly to scientists, operators, engineers, customers, regulators, and nontechnical stakeholders.

Requirements

An advanced degree in meteorology, atmospheric science, applied mathematics, statistics, physics, or a related quantitative field, or equivalent evidence of exceptional quantitative meteorological ability.
Strong understanding of cloud and precipitation processes, mesoscale meteorology, and numerical weather prediction.
Experience applying statistical methods to noisy, spatially and temporally correlated environmental data.
Strong Python and scientific-computing skills, including experience with tools such as NumPy, SciPy, pandas, xarray, and geospatial libraries.
Experience working with meteorological data such as GRIB, netCDF, radar, satellite, model, sounding, aircraft, or surface observations.
Ability to formulate ambiguous scientific and operational questions as measurable quantitative problems.
Experience building reproducible analyses, automated workflows, datasets, or decision-support tools.
Strong judgment about causality, confounding, uncertainty, validation, and the limits of observational evidence.
Clear written and verbal communication across scientific, operational, engineering, and commercial teams.
High agency and willingness to do the analytical and implementation work personally.

Nice to have

A PhD in meteorology, atmospheric science, or a closely related field.
Experience with cloud microphysics, orographic precipitation, convective precipitation, weather modification, hail, or field campaigns.
Experience with WRF, HRRR, GFS, ECMWF products, data assimilation, ensembles, operational forecast verification, or meteorological post-processing.
Experience with causal inference, experimental design, Bayesian methods, spatial statistics, time-series analysis, uncertainty quantification, or decision science.
Experience developing statistical or ML models for weather, remote sensing, or physical systems.
Familiarity with radar meteorology, satellite retrievals, quantitative precipitation estimation, cloud-particle measurements, or atmospheric instrumentation.
Experience designing or evaluating operational meteorological programs.
Experience communicating quantitative results to customers, regulators, government agencies, or business-development teams.

Benefits

Significant stock options with high potential upside as an early-stage company
401(k) with employer matching
Full health coverage (medical, dental, and vision insurance)
Relocation assistance provided (if applicable)
Unlimited PTO
Paid parental leave for both parents
Lunch provided when working in-office and a fully stocked kitchenette
Free EV charging at the HQ