ASTERRA is a successful earth observation company, based on Utilis technology, with headquarters in Israel and offices in the USA and UK. Come work at a place with true impact on the lives of millions. ASTERRA uses synthetic aperture radar (SAR) data from satellites or aircraft platforms to detect soil moisture underground with applications for infrastructure in the markets of water utilities, transportation, and property management.
ASTERRA R&D department seeks for a strong individual, problem solver with high motivation to join our growing Data Science & AI algorithm team. The selected applicant will be a part of the Utilis innovation cohort taking part in the company AI development and data analysis on unique datasets from satellites.
- Get dirty with our unique radar satellite imagery data.
- Participate in continuous data studies, working closely with other science and business teams, to address our customers’ various global resource management challenges.
- Prototype data products, and design field tests to be carried out by dedicated crews.
- Research and develop state of the art computer vision and deep learning algorithms to be applied on satellite imagery and geospatial datasets.
- Work closely with other departments to deploy and monitor our data products, delivering advanced data-based solutions to our customers, end-to-end.
- Communicate insights based on your work and be part of a committed scientific community.
- Sc. or M.Sc. graduates in Computer Science/Electrical Engineering/Math or other computational/quantitative fields from leading institutes. Equivalent relevant experience to be considered.
- Strong background in statistics.
- Proficiency in programming in Python and SQL.
- Basic competence in statistical programming with NumPy, Pandas, and scikit-learn, or in R.
- Background in Machine Learning and Computer Vision.
- Familiarity with Deep Learning frameworks such as TensorFlow or PyTorch.
- Excellent written and oral communications skills in English.
- A mindset for science, learning, and growth.
- Advanced academic degree.
- Experience in modern object-oriented and functional programming languages.
- Experience in Computer Vision and Image Processing.
- Experience with geospatial data and Python libraries such as GDAL, GeoPandas, Rasterio.
- Experience with Remote Sensing, geospatial analytics and GIS development.
- Experience with geospatial databases such as PostGIS.
- Experience with cloud computing environments such as AWS.