Senior Geospatial Data Scientist

at  THE MITRE CORPORATION

Why choose between doing meaningful work and having a fulfilling life? At MITRE, you can have both. That’s because MITRE people are committed to tackling our nation’s toughest challenges—and we’re committed to the long-term well-being of our employees. MITRE is different from most technology companies. We are a not-for-profit corporation chartered to work for the public interest, with no commercial conflicts to influence what we do. The R&D centers we operate for the government create lasting impact in fields as diverse as cybersecurity, healthcare, aviation, defense, and enterprise transformation. We’re making a difference every day—working for a safer, healthier, and more secure nation and world. Our workplace reflects our values. We offer competitive benefits, exceptional professional development opportunities, and a culture of innovation that embraces diversity, inclusion, flexibility, collaboration, and career growth. If this sounds like the choice you want to make, then choose MITRE—and make a difference with us.

DEPARTMENT SUMMARY:

MITRE’s Data Science department (L172) is looking for qualified applicants to bring their geospatial, machine learning, advanced analytics, and applied research skills to bear on solving problems of critical national importance. MITRE’s diverse work program provides opportunities to apply your expertise and creative thinking in challenging domains such as healthcare, transportation, and national security. Employees may also participate in MITRE’s internal research and development program, which provides funding for innovative applied research that addresses our sponsors’ hardest problems.

JOB DESCRIPTION:

The successful candidate for this position is a geospatial data scientist who combines a solid theoretical and technical background with the ability to formulate problems, develop and evaluate solutions, and communicate results. Familiarity with advanced geospatial data science, modeling, and analysis techniques and methods (e.g., supervised and unsupervised machine learning, GeoAI, Geosimulation, patiotemporal graphs) is a plus. Hands-on software development skills are a must. Candidates should have a strong understanding of how to engineer spatial solutions for geospatial systems and architecture in both traditional and cloud computing environments. Lifelong learning and keeping up with the latest research and technologies is an essential part of working in this field. Roles and responsibilities include:

• Support the development of geospatial data science, modeling, analysis, visualization, and engineering deliverables for sponsor projects and programs, internal research and development, and corporate strategic initiatives.
• Remain current on open-source, industry, academia, and US Government techniques and tools for geospatial data science, modeling, analysis, visualization, and engineering.
• Apply a variety of spatial data science techniques to tackle customer challenges to include geospatial statistics, spatial optimization, spatial pattern analysis, geospatial artificial intelligence, spatial autocorrelation, activity-based intelligence, imagery analysis, remote sensing, and geospatial data visualization approaches.
• Build and test geospatial prototypes in MITRE, government, and commercial cloud environments.

BASIC QUALIFICATIONS:

• Bachelor’s degree in Geospatial Data Science, Geospatial Intelligence, Geographic Information Systems, GeoInformatics, Computer Science, Mathematics, or related degree.
• Minimum of 5 years of experience with a bachelor’s degree or 3 years of experience with a master’s degree, or a PhD with relevant hands-on experience using Geospatial data science techniques.
• Ability to obtain Top secret clearance
• Applied experience with common GIS tools, developing geospatial workflows, and visualizations using Python.
• Applied experience in spatial analysis and modeling, and ETL of spatiotemporal datasets and managing spatial databases.
• Applied experience in the configuration of web-mapping, dashboard applications, and remotely sensed data.
• Familiarity with geostatistics, spatial machine learning, geosimulation, or GeoAI, and multispectral and hyperspectral imagery or synthetic aperture radar.
• Familiarity working with spatiotemporal data in graph databases, such as ArcGIS Knowledge, Neo4j, or ArangoDB.
• Familiarity developing web applications with common libraries, e.g. OpenLayers, Leaflet, ArcGIS JS API.
• Familiarity with geospatial data architectures and spatial database design and management, as well as containerization concepts.
• This position requires a minimum of 50% hybrid on-site.

PREFERRED QUALIFICATIONS:

• Active TS/SCI with polygraph.
• Advanced degree in Geospatial Data Science, Geospatial Intelligence, Geographic Information Systems, GeoInformatics, Computer Science, Mathematics, or related degree.
• Applied experience with other software development languages, e.g., C++, Java, C#, JavaScript.
• Applied experience with spatiotemporal big data technologies, e.g., GeoMesa, GeoTrellis, Data Bricks, or GeoSpark (Apache Sedona).
• Applied experience with data architecture containerization concepts, e.g. Docker or Kubernetes.
• Applied experience working with remotely sensed data to include aerial and satellite imagery, multi- and hyper-spectral imagery, LiDAR, or synthetic aperture radar.
• Applied experience with applying spatial modeling and analysis techniques to the atmospheric, climate, marine, oceanic, hydrologic, geomorphologic, critical infrastructure, transportation, network, telemetry, or terrain domains.

• Support the development of geospatial data science, modeling, analysis, visualization, and engineering deliverables for sponsor projects and programs, internal research and development, and corporate strategic initiatives.
• Remain current on open-source, industry, academia, and US Government techniques and tools for geospatial data science, modeling, analysis, visualization, and engineering.
• Apply a variety of spatial data science techniques to tackle customer challenges to include geospatial statistics, spatial optimization, spatial pattern analysis, geospatial artificial intelligence, spatial autocorrelation, activity-based intelligence, imagery analysis, remote sensing, and geospatial data visualization approaches.
• Build and test geospatial prototypes in MITRE, government, and commercial cloud environments