Strong background in geospatial data science and analysis techniques.
Experience with earth observation data, including optical and SAR imagery.
Familiarity with computer vision techniques for object detection and classification.
Proficient in Python and the machine learning lifecycle.
Ability to work independently and tackle ambiguous problems.
Responsibilities
Develop and enhance geospatial models that integrate AIS data with satellite imagery.
Apply computer vision methods for vessel detection and classification.
Manage large-scale geospatial datasets to build and validate models.
Transition models from prototype to production on GCP.
Explore new data sources to improve maritime domain awareness.
Clearly communicate findings to both technical and non-technical audiences.
Collaborate with data science and engineering teams on infrastructure and data pipelines.
Benefits
Opportunity to work on cutting-edge geospatial technology.
Collaborative environment with a focus on innovation.
Engagement with diverse datasets and real-world applications.
Chance to influence maritime domain awareness solutions.
Full Job Description
About the role
The Senior Geospatial Data Scientist sits within Theia's data science team, working on the models and pipelines that turn satellite imagery and vessel-tracking data into a verified picture of activity. Day to day, that means fusing optical and SAR imagery with AIS and other data sources and building the detection and prediction models behind capabilities like dark vessel detection, AIS spoofing, ship-to-ship transfers, and vessel attribution. You'll take work from prototype through to production on GCP alongside engineering, and you'll be expected to explain your reasoning clearly.
What you'll do
Develop and improve geospatial models and pipelines that fuse AIS data with optical and SAR satellite imagery to detect vessel behavior, anomalies, and deceptive activity at sea.
Apply computer vision techniques to satellite imagery for vessel detection, classification, and attribution.
Work with large-scale geospatial and time-series datasets (AIS tracks, imagery, vessel metadata) to build and validate detection and prediction models.
Take models from prototype through to production, working with engineering to deploy on GCP.
Investigate new data sources and methods to close gaps in maritime domain awareness.
Communicate findings and model behavior clearly to both technical and non-technical stakeholders, including customers.
Collaborate closely with the wider Theia data science and engineering teams on shared infrastructure, data pipelines, and tooling.
What We're Looking For
What We're Looking For
Strong geospatial data science background, with demonstrated experience working with spatial data, coordinate systems, and geospatial analysis techniques.
Experience working with earth observation data, e.g. electro-optical or synthetic aperture radar (SAR).
Some computer vision experience (e.g., object detection/classification applied to imagery).
Strong Python skills and practical experience with the machine learning lifecycle: predictive modeling, classification, evaluation, and iteration.
Comfortable working independently, thinking through ambiguous problems, and explaining your reasoning and approach to others.
Nice to Have
Experience working with AIS (vessel-tracking) data - desirable, but not a deal-breaker if the rest of your background is strong.
Familiarity with GCP (BigQuery, Vertex AI) or equivalent cloud data platforms.
Experience with geospatial tooling and libraries (e.g., QGIS, GDAL, GeoPandas).
Experience with PyTorch, scikit-learn, or similar ML frameworks.
Background in maritime, defense, intelligence, or energy domains.
