Applied Scientist

The Solution Development Department at Synspective is responsible for developing models and algorithms which produce insights using multiple sources of data, including our own satellite data. To do this, we develop an analytics platform to produce geoscience insights efficiently and easily.

The Applied Analytics Unit focuses on developing analytics for various solutions, based on research and experiments, as well as making their results exploitable by a larger audience.

Responsibility

You will be integrated within a team of scientists to research, develop and improve models at the core of Synspective's solutions

Details of work

- Research algorithms and develop code to extract insights from SAR imagery.
- Determine a suitable approach for each problem based on literature review and trials. Various tools can be utilized such as image processing, statistical learning, deep learning, etc
- Enrich your models by considering other types of information alongside SAR images (optical satellite, infrastructure polygons, weather data, etc)
- Closely collaborate with other scientists and also business members to find suitable solutions to various requests or issues.
- Utilize version control systems like Git to manage software code and collaborate with team members efficiently.
- Help finding and developing suitable visualization for various models and solutions.
- Continuously improve your skills and those of your team.

Selling points of this role

- Work on a daily-basis on imagery produced by Synspective's satellite constellation
- Collaborate alongside highly skilled engineers and scientists in a global setting.
- Participate in the development of state-of-the art approaches solving concrete issues related to sustainability, disaster prevention and management, etc.
- Some freedom is given to employees on the nature of their tasks and how they solve the various issues assigned to them.
- Synspective provides support for learning new skills and passing various certifications

- Bachelor’s Degree in Data Science, Statistics, Computer Science, or related field.

- At least 2-3 years of professional experience with Python and its scientific ecosystem (NumPy, Pandas, Jupyter, etc.)

- At least 2-3 years of professional experience working in a Unix environment and with Git

- At least 2-3 years of professional experience with statistics and machine learning.

- Ability to conduct literature surveys and quickly reproduce approaches from scientific papers.

- Motivation to learn new things and share them with the team.

Preferred qualifications

- Master’s Degree in Data Science, Statistics, Computer Science, or related field.
- Experience with SAR data and utilizing it in earth observation applications.
- At least 2-3 years of professional experience with machine learning and deep learning frameworks such as Scikit-Learn, pytorch etc
- At least 2-3 years of professional experience with GIS libraries such as GDAL and Rasterio.
- Fluent oral and written communication skills in English to convey techniques and results of analyses clearly to both experts and non-experts.