Earth Observation Data Scientist
Direct Entry Job 6 months Harwell, UK
Uploaded 22 Dec 2018
Spottitt provides self service satellite analytics for the energy, environment and infrastructure sectors. The Spottitt team have developed a range of automated analyses based on optical satellite imagery, ranging from land cover to building recognition, which are tailored to the renewable energy sector and the needs of a number of paying clients.
The main tasks of the role include:
- Lead the EO technical development work required to complete the development, accuracy & reliability testing and commercial launch of new services based on both optical and SAR satellite imagery. This development work includes elements such as change detection, automated feature extraction and automated classification.
- Work closely with our software development partners in Poland on the automation and service delivery of developed algorithms.
- To give technical input to the team with regards to the repackaging of existing services/algorithms for new markets.
- Developing prototype and proof of concept systems to demonstrate business need.
- To participate in end user detailed design workshops
- To deliver end user training on existing and newly developed service
- To maintain awareness of evolving EO and data science technologies and techniques.
- Continuous improvements to automated data handling tools
- To support the development and training of colleagues in the area of EO and data science, where relevant.
The role is initially for a six-month period with view to conversion to a permanent contract.
We are looking for candidates with the following skills and experience:
- Degree in Applied Remote Sensing or related fields.
- Proven self starter and problem solver able to break down big problems into steps.
- Proven experience in applied use of optical Earth Observation data to develop algorithms from initial concept to productisation / commercialistion. Proven experience in use of SAR data would be a big plus.
- Strong capabilities in the use of open source Earth Observation toolboxes such as RSGIS Lib, SNAP and therefore ability to code in Python.
- Strong capabilities in the use of QGIS.
- Experience of ENVI commercial image processing software package.
- Capable of identifying existing data sources to integrate within a service, such as sourcing relevant soil, weather, climate and / or historical disaster events datasets.
- Strong oral and written communication skills in English.
- Innovation and technology fan.
- Applications from able, driven, recent graduates will be considered.