Research Engineering Expert – Earth Sciences

• Convert real-world Earth-science research workflows into well-defined, self-contained terminal-based benchmark tasks
• Prepare and process climate, atmospheric, geological, hydrological, oceanographic, remote-sensing, and other environmental datasets
• Build reproducible environments using scientific libraries, command-line utilities, and domain-specific tools
• Create reliable expert solutions using Python, R, Bash, Julia, or other relevant scientific programming languages
• Develop tasks involving geospatial analysis, numerical simulation, time-series processing, interpolation, forecasting, remote sensing, and environmental risk assessment
• Define objective evaluation criteria for scientific outputs, numerical accuracy, data transformations, model behavior, and spatial or temporal correctness
• Verify coordinate reference systems, measurement units, timestamps, missing-data handling, scientific assumptions, and numerical consistency
• Develop automated tests for numerical tolerances, output formats, metadata, reproducibility, and task requirements
• Diagnose and resolve issues involving geospatial projections, large datasets, dependencies, computational performance, and numerical stability
• Document data provenance, task instructions, expected outputs, edge cases, scientific limitations, and validation procedures
• Complete the initial application and interest confirmation
• Complete a 120-minute technical assessment
• Work with delivery managers through application and assessment review

• PhD in an Earth Sciences discipline is mandatory, including climate science, atmospheric science, geophysics, oceanography, geology, hydrology, remote sensing, environmental modeling, or Earth-system science
• Strong expertise in at least one Earth-science specialization, supported by academic research or relevant professional experience
• Proficiency in Python, C/C++, MATLAB/Octave, Julia, or similar programming languages used for scientific simulation, modeling, and data analysis
• Hands-on experience with scientific data processing, numerical modeling, geospatial analysis, environmental datasets, or time-series analysis
• Experience developing, debugging, and validating computational workflows
• Comfort working independently in Linux and terminal-based environments
• Strong understanding of scientific quality control, spatial and temporal data, uncertainty, and numerical accuracy
• Excellent analytical, problem-solving, and technical documentation skills
• Available to begin immediately
• Ability to commit to approximately 40 hours per week and at least 4 hours of daily overlap with PST
• Ability to complete a 120-minute technical assessment
• Must use the same email address for the Interest Check Form and agency portal submission

• No medical benefits
• No paid leave
• Contract duration: 5 weeks
• 40 hours per week
• At least 4 hours of daily overlap with Pacific Standard Time (PST)