Earth-Science Computational Research Engineer

Crossing Hurdles; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

Crossing Hurdles is seeking a scientifically rigorous researcher to translate Earth-science workflows into reproducible benchmark tasks. You will prepare diverse geoscience datasets and build self-contained computational environments with scientific libraries and command-line tools.

You will create robust solutions using Python, R, Bash, Julia, or domain software, and define objective criteria for model outputs, data transformations, and spatial/temporal accuracy.

Qualifications

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in Earth Sciences or a closely related field.
• Strong programming skills in Python, R, Julia, Bash, or another scientific programming language.
• Hands-on experience with scientific data processing, numerical modeling, geospatial analysis, environmental datasets, or time-series analysis.

Responsibilities

• Translate authentic Earth-science workflows into self-contained terminal benchmark tasks.
• Prepare geospatial, climate, atmospheric, geological, hydrological, and oceanographic datasets.
• Build reproducible computational environments with appropriate scientific libraries and command-line tools.
• Create expert solutions using Python, R, Bash, Julia, or domain-specific software.
• Develop tasks involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, and environmental risk analysis.
• Define objective grading criteria for scientific outputs, model behavior, data transformations, and spatial or temporal accuracy.

Skills

Earth sciences

Geospatial data

Python

R

Julia

Bash

Linux

Time-series analysis

Remote sensing

Numerical modeling

Education

Ph.D., postdoc or equivalent advanced experience in Earth Sciences

Tools

NumPy

pandas

SciPy

xarray

rasterio

GeoPandas

Cartopy

GDAL

Job description

Crossing Hurdles is seeking a scientifically rigorous researcher to translate Earth-science workflows into reproducible benchmark tasks. You will prepare diverse geoscience datasets and build self-contained computational environments with scientific libraries and command-line tools.

You will create robust solutions using Python, R, Bash, Julia, or domain software, and define objective criteria for model outputs, data transformations, and spatial/temporal accuracy.