
Data Scientist for Geospatial Applications
3 days ago
We are seeking a skilled geospatial data scientist to collaborate closely with customers, understanding their business needs and developing innovative solutions using ESRI products.
The ideal candidate will have strong Python programming skills, proven data science and AI expertise, and experience in machine learning, deep learning, and geospatial analysis.
- Work collaboratively with customers to comprehend their requirements and design tailored data science solutions.
- Develop high-performance analytics systems that tackle complex geospatial challenges by applying techniques from data mining, statistics, and machine learning.
- Design and deploy predictive models utilizing popular deep learning libraries like PyTorch and integrate ArcGIS with these libraries.
- Perform feature engineering, model selection, and hyperparameter optimization to achieve high predictive accuracy.
- Implement best practices and patterns for geospatial machine learning and create reusable technical components.
- Collaborate with cross-functional teams to design and deliver solutions.
Key qualifications include:
- At least 5 years of hands-on experience in machine learning or relevant academic/lab work.
- Proven data science and AI skills with Python, PyTorch, and Jupyter Notebooks.
- Experience in building and optimizing supervised and unsupervised machine learning models.
- Expertise in one or more areas: traditional and deep learning-based computer vision techniques, convolutional neural networks, transformer models, 3D deep learning, and applied statistics concepts.
- Ability to extract, transform, load, and visualize data using various libraries.
Essential skills include:
- Master's degree in RS, GIS, Geoinformatics, or a related field with knowledge of RS & GIS.
- Knowledge and experience of ESRI products like ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise.
- Strong communication skills, including to non-technical audiences.
- Strong Python coding skills and ability to learn new technologies quickly.
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