Lead Data Scientist developing AML transaction - monitoring models for RBC, a major Canadian bank. Applying machine learning, rules, and analytics to identify financial crime risk.
About the role
- Senior Geo Data Scientist developing advanced machine learning models for geospatial applications at VRIFY. Transforming complex geospatial data into actionable predictions for mineral exploration decisions.
Responsibilities
- Design and deploy machine learning models for geospatial applications, including deep learning architectures (e.g., Vision Transformers, GNNs) applied to high-dimensional raster and spatial datasets.
- Develop scalable data pipelines for geospatial data, including preprocessing, feature engineering, sampling strategies, and spatial cross-validation.
- Build and maintain end-to-end ML workflows, ensuring reproducibility, performance optimization, and reliable generation of actionable predictions.
- Develop custom geospatial models that capture real-world spatial patterns to improve prediction accuracy and support decision-making.
- Engineer geospatial features that reflect spatial relationships and domain-specific characteristics to enhance model performance.
- Apply and advance model interpretability techniques to understand spatial patterns and quantify feature influence in complex ML models.
- Use tools like Google Earth Engine and Hugging Face to process large-scale geospatial data and integrate modern AI models into production workflow
Requirements
- BSc, MSc, or PhD in Computer Science, Engineering, Geoscience, or a related field, or equivalent practical experience
- 5+ years of experience in machine learning, data science, or software development, including production ML systems
- Strong experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow, JAX, scikit-learn)
- Deep understanding of machine learning architectures (e.g., transformers, vision transformers) and approaches such as clustering and ensemble methods
- Strong programming experience in at least one high-level language (e.g., Python)
- Experience building and deploying machine learning models in production environments
- Experience working with geospatial data (e.g., raster data, satellite imagery, spatial datasets)
Benefits
- Health Benefits: Extensive coverage, medical, dental, and vision plans.
- Paid Time Off (PTO): Including vacation days, sick days, personal days, public holidays plus extra time during holiday season.
- Work-Life Balance: Flexible work hours, remote work options plus option to use work space in Downtown Vancouver (free snacks & gym).
- Professional Development: Career growth program to help our team unlock their potential and advance their career.
- Performance Bonuses
- Wellness Programs: Fitness allowance, work from home allowance, mental health support.
- Retirement Plan (RRSP/DPSP)
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