The Data Scientist will analyze hyperspectral satellite imagery, develop machine learning models, and build data pipelines to derive insights.
Job Description
The Data Scientist will develop advanced analytics models that extract valuable insights from hyperspectral satellite imagery. The role involves applying machine learning and statistical techniques to identify materials, environmental patterns, and industrial signals from spectral data.
Key Responsibilities
- Analyze hyperspectral satellite datasets to detect materials and environmental patterns.
- Develop machine learning models for classification, anomaly detection, and predictive analysis.
- Design algorithms that identify spectral signatures for agriculture, mining, and environmental monitoring.
- Build data processing pipelines for training and validating AI models.
- Collaborate with engineers to deploy models into production systems.
- Conduct exploratory data analysis to improve algorithm performance.
- Present insights and technical findings to internal teams and stakeholders.
Requirements
- Master’s or PhD in Data Science, Remote Sensing, Physics, or a related field.
- Strong experience with Python, NumPy, Pandas, and Scikit-learn.
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
- Understanding of hyperspectral or multispectral imagery.
- Strong statistical analysis and data visualization skills.
Top Skills
Numpy
Pandas
Python
PyTorch
Scikit-Learn
TensorFlow
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