Research Scientist II, Step 1-4

University of Alabama in Huntsville; Huntsville (AL); Hybrid; USD 67,000 - 90,000; Full time

Job summary

The University of Alabama in Huntsville seeks a Data Science Research Scientist for the EarthRISE Project Office. You will co-develop Earth-observation driven data solutions, integrate Geo-AI workflows, and support cross-cutting needs across the EarthRISE program.

The ideal candidate has strong background in computer science, remote sensing, ML, cloud computing, and LLM/Geo-AI integration, and will collaborate with NASA centers, publish results, and contribute to workforce development in

Qualifications

• 4+ years of experience in these disciplines is desired.
• Experience with NASA and/or other federal, state, local, tribal, or private sector organizations is desired.
• Earth science geospatial data analysis experience, including math, statistical & scientific data processing automation, and raster data processing of temporal datasets is desired.
• Experience integrating AI systems with cloud-native geospatial platforms including STAC APIs, CO-Gs, Earthdata services, Google Earth Engine, AWS Open Data, and distributed geospatial processing environments is desired.
• Experience in writing and developing technical manuscripts is desired.
• Record of publication commensurate with level of experience is desired.
• Experience integrating multimodal AI and foundation models including Vision Transformers (ViTs), Earth Observation Foundation Models, multimodal LLMs, and geospatial deep learning architectures for image, raster, and text analysis is desired.
• Demonstrated ability to develop and validate autonomous scientific decision-support systems by combining Earth Observation datasets, statistical methods, machine learning, and LLM-based reasoning to support operational and policy-relevant applications is desired.
• Experience in developing, tuning, and deploying machine learning-based algorithms, including geospatial artificial intelligence to address real-world problems is desired.
• Strong experience teaching, skills building, curriculum development, knowledge management, and workforce development is desired.

Responsibilities

• Provide Data Science and technical expertise across a set of thematic areas in support of EarthRISE.

Skills

Data science

Geo-AI

Machine learning

Cloud computing

Geospatial analysis

Remote sensing

Geospatial workflows

LLM integration

Scientific publications

Team collaboration

Tools

STAC APIs

COGs

Earthdata services

Google Earth Engine

AWS Open Data

Distributed geospatial processing

Job description

Job no: 504208
Department: Earth System Science Center
Work type: Staff Full-time Exempt
Location: Alabama
Categories: Research - Computer Science, Research - Environmental

Purpose of the Position:

The EarthRISE Project Office, within the Lab for Applied Science (LAS) under the Earth System Science Center (ESSC), is seeking a highly motivated Data Science Research Scientist with applied experience in computer science, geospatial artificial intelligence (Geo-AI), machine learning, cloud computing, and remote sensing/geospatial datasets to join our interdisciplinary science team. The Data Science Research Scientist will play a key role in the team by co-developing Earth-observations-driven data solutions and geospatial artificial intelligence-informed services and supporting workforce development activities in support of the EarthRISE program. The Data Science Research Scientist will also be responsible for supporting an array of cross-cutting thematic needs in expanding the applied research portfolio of EarthRISE’s Data Science efforts as well as LLM and Geo-AI Integration. A successful candidate will have a strong background in the fields of computer science, remote sensing, agentic workflows, and machine learning algorithms. As part of our diverse, highly dynamic group, you will work side-by-side with a team of exceptional scientists to translate Data Science into actionable insights for decision-makers and stakeholders, while fostering your career growth and development.

EarthRISE is a project of the National Aeronautics and Space Administration (NASA) that works in collaboration with state, local, tribal, territorial, and private sector partners to use information provided by Earth observing satellites and geospatial technologies for managing environmental challenges. EarthRISE’s goal is to empower decision-makers with tools, products, geospatial artificial intelligence, and services to act locally on issues across many thematic areas including disasters, agriculture, water, ecosystems, air quality, and health.

The EarthRISE Project Office in Huntsville, AL, offers a flexible and dynamic work environment, with an in-house team of over 30 science professionals and numerous opportunities for growth and professional development. With a growing economy, diverse population, low cost of living, and vibrant city life, Huntsville is consistently ranked among the top places to live in the U.S.

Duties / Responsibilities:

A Data Science Research Scientist plays a key role in co-developing and evaluating Geo-AI LLM-integrated geospatial workflows and/or robust, predictive models and delivering cutting-edge scientific breakthroughs to decision makers.

• Provide Data Science and technical expertise across a set of thematic areas in support of EarthRISE.
• Work together with the Data Science team as well as the program Chief Scientist and activity managers to provide strategic guidance to EarthRISE office on integration of emerging data science best practices in end-user solutions.
• Support EarthRISE office throughout the project lifecycle (planning, execution, and follow-up) to catalyze the use of advanced data science techniques in support of end-user solutions.
• Support or lead open science work via publications, special journal issues, data products/services, and presenting at scientific conferences.
• Contribute to or lead scientific publications.
• Coordinate and collaborate with broader EarthRISE teams at MSFC and other NASA centers.

Desired Qualifications:

• 4 or more years of experience working in these disciplines is desired.
• Experience working with NASA and/or other federal, state, local, tribal, or private sector organizations is desired.
• Earth science geospatial data analysis experience, including math, statistical & scientific data processing automation, and raster data processing of temporal datasets is desired.
• Experience integrating AI systems with cloud-native geospatial platforms including STAC APIs, Cloud Optimized GeoTIFFs (COGs), Zarr, Earthdata services, Google Earth Engine, AWS Open Data, and distributed geospatial processing environments is desired.
• Experience in writing and developing technical manuscripts is desired.
• Record of publication commensurate with level of experience is desired.
• Experience integrating multimodal AI and foundation models including Vision Transformers (ViTs), Earth Observation Foundation Models, multimodal LLMs, and geospatial deep learning architectures for image, raster, and text analysis is desired.
• Demonstrated ability to develop and validate autonomous scientific decision-support systems by combining Earth Observation datasets, statistical methods, machine learning, and LLM-based reasoning to support operational and policy-relevant applications is desired.
• Experience in developing, tuning, and deploying machine learning-based algorithms, including geospatial artificial intelligence to address real-world problems is desired.
• Strong experience teaching, skills building, curriculum development, knowledge management, and workforce development is desired.

Published Salary (if available):

$67,151-$89,611

Advertised: Jul 28 2026 Central Daylight Time
Applications close:

Please note, job openings are posted for a minimum of three (3) business days and may be removed from the job posting board and filled any time after the minimum posting period has ended.

The University of Alabama in Huntsville is an equal opportunity employer (EOE), including an EOE of protected veterans and individuals with disabilities.