Applied Scientist

Role:

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

Responsibilities:

• 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:

• 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 to solving concrete issues related to sustainability, disaster prevention, 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

Minimum Qualifications:

• 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.