6-month Earth Observation Data Scientist Internship - Climate Tech
Work on high-impact projects and innovate new solutions to problems in the earth observation space
Data modelling
London, United Kingdom (remote)
Company Size
1-10 employees
1-2 years
Employment Type
6 months
~2 months ago


What is Sylvera anyway?

‍Sylvera is scaling carbon markets with software. Sylvera does this by applying advanced machine learning techniques to satellite data to quantify with unprecedented accuracy the amount of carbon stored in landscapes. We also provide a holistic picture of offset projects, providing people with the information they need to make informed decisions.By providing transparency, Sylvera intends to underpin functioning voluntary carbon markets. This will allow the market to scale to keep the planet under 2C of warming, and unlock huge co-benefits for nature and society.

What will I be doing? ‍‍

  • Work on high-impact projects and innovate new solutions to problems in the earth observation space
  • Work closely with computer vision and machine learning engineers to process data from various satellite sources
  • Develop cutting-edge machine learning classifiers, models and algorithms operating on visual data


What do I need? 

  • BSc or MSc in Computer Science or a related technical field or relevant work experience
  • Experience writing modular code in Python (through internships, work experience or personal projects)
  • Experience building quick prototypes and following data-driven iteration
  • Experience working with Satellite data, aerial data or other geospatial data products
  • To care about the climate and ecosystems of Earth, and to want to change incentives so they get valued and protected.

Brownie points for?

  • Experience solving problems with Machine Learning using Deep Learning tools such as Tensorflow or PyTorch
  • Exposure to Google Earth Engine, aerial images
  • Exposure to SAR or LIDAR data


>London Living wage


London, or remote +/- 4hours to GMT

To apply, please follow the application process here.