RCUH is looking to hire a Machine Learning Technician to enhance the collection and application of hydrologic data, specifically for climate and environmental forecasting.
Requirements
- Strong knowledge of climate science concepts, machine learning methods, geospatial analysis, and statistical modeling.
- Strong ability to design and implement data pipelines, develop and optimize machine learning models, and program in languages such as Python or R.
- Experience with cloud computing platforms (e.g., AWS, Google Cloud) and high-performance computing environments.
- Familiarity with hydrologic and climate models used in Pacific Island contexts.
- Experience developing APIs or user-facing tools for scientific data.
Responsibilities
- Assists with designing, building, and maintaining data pipelines for climate and environmental datasets to support operational forecasting.
- Assists with developing and optimizing machine learning models to improve climate and environmental prediction and forecasting capabilities.
- Conducts statistical analysis, model validation, and quality assurance to ensure reliability and accuracy of results.
- Creates and maintains software tools, APIs, and databases to enable efficient access and use of research outputs.
- Prepares documentation, technical reports, and presentations.
- Collaborates with scientists, policymakers, and other stakeholders to translate research into practical solutions.
- Contributes to training and mentoring of students and early-career researchers in machine learning, data science, and environmental modeling.
Other
- Bachelors Degree from an accredited four (4) year college or university in Computer Science, Data Science, Environmental Science, or related field.
- Up to one (0-1) year of experience working with machine learning and environmental data.
- As a condition of employment, employee will be subject to all applicable RCUH policies, procedures, and trainings and, as applicable, subject to University of Hawaii's and/or business entity's policies, procedures, and trainings.
- Please go to https://www.rcuh.com/opportunities/job-openings/. You must submit the following documents online to be considered for the position: 1) Cover Letter, 2) Resume, 3) Professional References, 4) Copy of Degree(s)/Transcript(s)/Certificate(s).
