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Data Science Intern (3 months)

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Job Description

About Agreena

Agreena is an exciting, dynamic, and purpose-oriented organisation united in a mission to mobilise farmers and corporations to unlock the value of nature and help restore the planet. While we’re rooted in agriculture, finance, and technology, our team of experts range from soil carbon scientists and software developers to market strategists and regulatory affairs experts. Over 200 employees across more than 40 nationalities are gathered under the common Agreena flag – either working from our headquarters in Copenhagen, offices in London, or remotely across Europe.


Agreena provides solutions that drive both environmental and financial sustainability. Our company offers a supportive and positive work environment with opportunities for learning, leading, and growth no matter where you are in your professional journey. We believe in giving our employees a lot of responsibility, and we encourage new thinking, innovation, and fun.


And this is where you come in:

The Data Science Team at Agreena focuses primarily on the development and research for our suite of Monitoring and Remote Verification (MRV) capabilities. Leveraging remote sensing inputs such as satellite imagery, and additional data sources such as weather and soil data, these MRV capabilities monitor global regenerative farming practices at scale. You will apply your analytical and technical mindset to support the development of these technologies including; assisting in exploratory data analysis, data visualisation, dataset curation, model training, and performance testing. You will have the opportunity to collaborate closely with our Data Engineering and Machine Learning Operations Teams to understand the development life-cycle of machine learning technologies from the research and development stage, to a fully automated and productionised system.


We are looking for someone who is located in the London area and can come to the office a few times a week.

This internship is unpaid, for the duration of 3 months.

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