Data Scientist - AI/ML

Responsibilities

• Design, develop, and deploy machine learning and artificial intelligence models to support predictive analytics, environmental monitoring, geospatial intelligence, and Earth science research applications.
• Develop geospatial analytics, visualization tools, and web-based applications for large environmental and remote sensing datasets.
• Create and support RESTful APIs, web services, and cloud-based data access systems utilizing AWS and Azure cloud platforms for scalable storage, processing, and dissemination of Earth science data.
• Develop workflows for processing, quality control, analysis, and dissemination of satellite-derived geospatial products.
• Collaborate with scientists to translate research requirements into operational software solutions.
• Support Earth science data archives, user services, and community engagement activities.
• Perform spatial and temporal analysis of environmental datasets using GIS, remote sensing, and statistical methods.
• Develop and automate data processing pipelines using Python and scientific computing frameworks, leveraging cloud services to support large-scale geospatial and remote sensing workflows.
• Integrate diverse datasets from satellite observations, field measurements, and numerical models.
• Prepare technical documentation, scientific reports, conference presentations, and peer-reviewed publications.
• Collaborate with scientists, software engineers, and technology partners to identify opportunities for integrating quantum computing concepts into AI/ML workflows, high-performance computing environments, and next-generation Earth science applications.

Requirements

• Master’s Degree (M.S.) and a minimum of 5 years related experience and/or training, or equivalent combination of education and experience.
• Experience applying AI/ML techniques to Earth science, climate, environmental, geospatial, remote sensing, or other large scientific datasets.
• Strong programming skills in Python and experience with scientific computing workflows, including Fortran and high-performance computing environments.
• Experience developing and deploying AI/ML solutions using cloud platforms such as AWS and Azure.
• Experience with GIS and geospatial data processing tools.
• Experience working with large environmental, remote sensing, or geospatial datasets.
• Knowledge of spatial databases, web services, application development frameworks, and emerging technologies such as quantum computing.
• Experience developing and supporting data visualization and analytics tools.
• Strong written and verbal communication skills.
• Ability to work effectively in multidisciplinary scientific teams.

Desired Qualifications

• Experience supporting NASA, NOAA, USGS, or other federal Earth science programs.
• Experience with satellite data products such as MODIS, Landsat, VIIRS, or similar Earth observation datasets.
• Experience developing geospatial web applications and cloud-enabled data services.
• Knowledge of GDAL, ArcGIS, GRASS GIS, or similar geospatial software packages.
• Experience with JavaScript, Node.js, SQL, Linux, and scientific computing environments.
• Experience with hydrologic, environmental, ecological, or climate modeling.
• Demonstrated record of peer-reviewed scientific publications.
• Experience interacting directly with scientific user communities and stakeholders.