Data Scientist
Tasks
- Build automated reporting systems
- Build data ingestion pipelines
- Build impact based forecasting systems
- Build predictive early warning models
- Create decision trees and recommendation engines
- Create ensemble models
- Design data architecture
- Develop interactive dashboards
- Develop machine learning and deep learning models
- Fine-tune foundation models
- Fuse multimodal data streams
- Implement computer vision for satellite imagery
- Implement reinforcement learning systems
- Monitor model performance and deploy models
- Train and fine-tune models
Perks/Benefits
Skills/Tech-stack
CNN | Change detection | Classification | Clustering | Computer Vision | Data Augmentation | Data Fusion | Data Generation | Deep learning | ETL | Earth Engine | Experiment tracking | Few-Shot Learning | Few-shot | GDAL | Geopandas | Geospatial analysis | Geospatial tooling | Google Earth | Google Earth Engine | Keras | Landsat | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Deployment | Multimodal Data | Multimodal data fusion | Natural Language | Natural Language Processing | NumPy | Object Detection | Pandas | Power BI | PyTorch | Python | Rasterio | Regression | Reinforcement Learning | SAR | SQL | Scikit-learn | Semantic Segmentation | Sentiment Analysis | Sentinel 1 | Sentinel 2 | Synthetic Data Generation | Synthetic data | Tableau | TensorFlow | Time Series | Transfer Learning | Transformer | Version control | Xarray
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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