Junior Data Scientist R&D M/F (6-month internship)

Passionate about Climate, Energy and AI? Join Kayrros, as a Junior Data Scientist R&D M/F (6-month internship)

Kayrros is a global climate technology company and the world leader in environmental intelligence.

Founded in 2016, it uses artificial intelligence and machine learning to analyze massive amounts of satellite imagery and other inputs at scale and generate standardized, near-realtime data on greenhouse gas emissions and energy supply chains used for trading, environmental compliance and reporting purposes, as well as bespoke data on emissions, climate risks, land-use change and other metrics used by public and private-sector actors such as asset managers, regulators, industrial and consumer-product companies, insurers and others in various proprietary applications. Kayrros technologies provide a powerful set of high-impact tools to reduce our climate footprint, manage climate risks, harden our resilience to extreme weather events, and accelerate the transition to a lower-carbon economy.

Kayrros’s accomplishments have earned it wide recognition. We have been named one of TIME‘s 100 Most Influential Companies, been featured on Fortune’s ‘Change the World’ list in both 2023 and 2024, named Top Five Company of the Year in Fast Company’s ‘World Changing Ideas’ 2024 awards, and won the Financial Times Tech Champion award.

We have offices in Paris, Houston, New York, London, Bangalore, and Singapore. Now, we’re looking to grow our outstanding team by hiring gifted individuals who want to disrupt global climate governance and shape the future of finance and the environment.

Join us to make a difference!

For more information, visit www.kayrros.com.

We are currently recruiting for our Paris office, a Junior Data Scientist R&D M/F (6-month internship)

The team you will be joining: Nature team

The Nature team is in charge of products and solutions for the monitoring of natural ecosystems and environmental risks. We produce datasets for public institutions, investors and insurance companies to reduce the environmental impact on the economy, scale conservation efforts and build efficient adaptation policies.

Abstract: The goal of the internship is to develop ML (DeepL) models to automatically classify different forest types (managed, natural, production) and detect deforestation and degradation from raw satellite imagery.

Role:

Data scientists play a key role at Kayrros, working both on R&D and discovery topics. Most of their work consists in developing models using various methods based on recent scientific papers including computer vision, machine and deep learning, and signal processing. They also collaborate with data engineers to build robust pipelines and work hand in hand with data analysts to analyze and visualize the results of their models. As part of the product team, Data Scientists are also expected to apply their models to various use cases, to build energy-related products.

They face two main challenges:

• The diversity and complexity of data available. Kayrros has a strong expertise in remote sensing and has been working with data from many different sensors (multispectral, hyperspectral, SAR, LIDAR, geostationary). Understanding the specificities of each technology and choosing the most appropriate for a given problem is therefore a crucial step.

• The complexity of the problems to solve: be it to provide a hedge on carbon credit markets or compute the right environmental risk metric, Kayrros navigates a space where the utmost rigor is required to bring value to its users.

As a Data Scientist, you will have to:

• Formulate problems considering available data and project constraints.

• Explore and review existing approaches or relevant associated scientific literature.

• Design, implement and test algorithms.

• Continuously provide ideas to improve products and take part in all team discussions.

• Help to apply your models to “real-life” use cases.

• Grow a culture around remote sensing data, as well as large datasets.

Requirements

Profile :

This is an ideal opportunity if you are looking for a six-month internship starting between January and July 2025, and you want to join an impactful company.

• You have a strong background and are passionate about image processing, machine learning, statistics, and operations research. You are very interested in various topics including deep learning, time series analysis, computer vision, and signal processing. You demonstrate experience in a least one of these areas

• You have strong programming skills in Python, SQL, Machine Learning libraries, data visualization packages and data manipulation. Previous exposure to Git is preferred.

• You are dynamic, curious and eager to learn.

• You can design and deliver working prototypes in a fast-paced environment and then put them into production with the help of data engineers

• You can communicate clearly in English, including with non-technical people

• You are willing to work in R&D that will be put to use as part of a product.

• You are willing to be an active member of the team and have a real impact on the company’s success

Why join Kayrros?

• We are a young, fast-growing tech company and are extremely passionate about what we do.

• We are located in the WeWork building on Rue la Fayette, 75009 (free drinks, events and a vibrant atmosphere).

• You will work with an international team and practice your English (or Chinese, German, Greek, Portuguese…) on a day-to-day basis.

References

• M3Fusion: A Deep Learning Architecture for Multiscale Multimodal Multitemporal Satellite Data Fusion

• TropiSCO : a project to monitor tropical deforestation with Sentinel-1 on a weekly basis

At Kayrros, we are committed to fostering an inclusive and diverse workplace. We believe in equal opportunities for all applicants, regardless of gender. We actively promote gender equality in all aspects of our recruitment process and encourage applications from individuals of all genders. If you don’t meet all the listed skills or qualifications, we still encourage you to apply.