Senior Geo Data Scientist is a Data Scientist role (full-time). with Zendesk. in REMOTE, JINDABYNE, AU. Compensation shown: $131K–$139K (est.). Imported listing (source: talentpulse.66ghz.com). Apply on the employer's site (talentpulse.66ghz.com).
Imported listing (source: talentpulse.66ghz.com) · Apply on talentpulse.66ghz.com
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Imported job description
Sourced from talentpulse.66ghz.com
VRIFY is seeking a Senior Geo Data Scientist to build ML systems that turn complex geospatial data into actionable predictions for mineral exploration. This role spans ingestion, feature engineering, model deployment, monitoring, and reliability, using modern AI methods such as Vision Transformers and GNNs. The position is a senior individual contributor role on a small, high-trust team, remote-first within Canada.
Responsibilities
Design and deploy ML models for geospatial applications, including Vision Transformers and GNNs on high-dimensional raster and spatial datasets.
Build scalable, automated data pipelines covering preprocessing, feature engineering, sampling, and spatial cross-validation.
Own end-to-end ML workflows: scheduling, monitoring, alerting, retraining, and reliability.
Develop custom geospatial models and features that capture real-world spatial patterns.
Apply model interpretability techniques to understand spatial patterns and feature influence.
Use Google Earth Engine, Hugging Face, and similar tools to scale geospatial AI in production.
Requirements
BSc, MSc, or PhD in Computer Science, Engineering, Geoscience, or a related field (or equivalent practical experience).
5+ years in ML, data science, or software development, including production ML systems.
Zendesk is a software-as-a-service company that provides an AI-first customer service platform. Its solutions are designed to simplify customer engagement and support by unifying communications across various channels such as email, chat, phone, and social media.
Strong Python and modern ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn).
Deep understanding of ML architectures (transformers, vision transformers, clustering, ensembles).
Experience applying deep learning (Vision Transformers, GNNs) to geospatial problems.
Hands-on experience with satellite imagery, raster data, and vector geospatial data, including coordinate reference systems, raster processing, and vector geometry operations; core library experience required (GeoPandas, Rasterio, GDAL).
Built and maintained production ML pipelines on a regular automated cadence with orchestration (Airflow, Dagster, Prefect), monitoring, alerting, and retraining.
Mandatory: demonstrated industry or academic research experience in mineral exploration, mining, geology, or earth sciences.
Track record of operating independently as a senior IC.
Benefits
Health insurancedental insurancevision insurancepaid time offflexible work hoursremote workprofessional developmentperformance bonuswellness programretirement plan