Data Scientist

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Soil Capital is on a mission to regenerate over 10 million hectares of land by 2030, addressing our environmental and food security challenges through regenerative and low-carbon agriculture. As a leading expert in this field, we have developed the first payment for ecosystem services program for farmers in Europe.

Through our certified programme and our platform, Soil Capital leads the food and ag sector transformation by engaging with blue chip organisations who seek to deliver on their environmental commitments and build supply chain resilience. These business purchase regenerative units, acting as an incentive for farmers to measure and earning improve their agricultural practices.

Our technology supports farmers by allowing them to efficiently and accurately measure farming practices, as well as the GHG balance of their farm which we then audit and certify to generate certificates. This helps farmers understand the levers to accelerate their adoption of regenerative practices.

In the past ten years, Soil Capital has established as a thought leader and a driver of change at scale in France, the U.K. and Belgium. Pursuing its ambitious growth trajectory, it is now expanding geographical and product scopes.

About the role

We are looking for a Data Scientist to expand our data team who can bring the most interesting pieces of data to life!

Data plays a crucial role for Soil Capitals innovation and growth. At Soil Capital we are collecting a relevant and genuine dataset on farming practices. We use this dataset to support the transition to Regenerative Agriculture from our farmers and corporate clients.

The Data team's main mission is to bring more data driven insights to the Soil Capital teams and clients.

The Data Scientist will identify new methods to leverage and expand our collected farmer data to support Soil Capital's mission. The role is exploratory and hands-on and will bring new innovative elements to our product, as well as to our farmers, partners and corporate clients.

• Play a leading role in creating value through data for Soil Capital. Projects here include, but are not limited to creation of agronomic insights for our internal agronomists and farmers, developing prediction and recommendation engines, computing environmental KPIs for corporate clients, …
• In the Data Science team we are exploring advanced ways to capitalize on our unique farm management dataset to provide extra value to our farmers, corporate clients and colleagues. The main data we use for this is our own dataset, combined with available third party data (governmental datasets, remote sensing products, map based data, …).
• The extra value we are looking for is for example integrating new science, new environmental KPIs, without adding encoding burden to our farmers, but based on opendata or satellite imagery.

Your main responsibilities will be to:

• Bring innovation to Soil Capital through data science and machine learning
• Perform technical data scientific work leading to data insights for our customers across the agri-food value chain. This will require being able to bridge the gap between science, agronomy and data, going beyond linear data reporting by fusion with machine learning, opendata, …
• Increase the use of our dataset to solve complex problems, including the empowering of other Soil Capital team members.
• Build, test, and maintain data engines for prediction, recommendation, scenario analysis and other tasks, in close collaboration with Soil Capitals stakeholders.
• Work in multidisciplinary teams to identify and challenge needs among clients and internal teams at Soil Capital. Translate these needs into innovative data products.
• Understand the value of our dataset as well as data gaps that if filled would create extra value to our users

The work of the data scientist will find its place in various use cases, such as reports for internal and external usage, protocols and methods to be included in our apps, reporting dashboards, presentations, cross-team and operational collaboration for the mySoilCapital programme.

This job will contain variation, ranging from fully exploratory projects to solving specific business problems through data. Key to this role is the ability to combine relevant scientific progress from academic sources with our farmer and general business needs in order to provide extra value to our clients. Communicate insights from complex data or algorithms into simple conclusions that will empower others to act based on the insights you derive

Skills & qualifications

• You have a heart and a fascination for agriculture and are committed to make a sustainable difference in this field.
• You are a candidate with MSc or equivalent level degree and proven experience in environmental data science, for instance agronomy, biology, geography, climatology, or related environmental sciences
• A successful candidate has a hands-on mindset, and is comfortable taking initiative and leading innovative developments, providing solutions for short, mid or long term business needs.
• You are able to digest scientific literature, derive insightful data methods from it and incorporate that in Soil Capital products
• This role will require strong data science skills in Python, machine learning is a plus
• Knowledge of PostgreSQL is a plus
• Candidates with experience with processing remote sensing data, or geospatial dataset have a plus
• Fluent in English

Why Join Soil Capital?

At Soil Capital, we believe that transforming our relationship with nature is the key to a viable food system. Farmers, as stewards of 40% of the Earth's land, hold the potential to lead this change. By joining us, you'll have the opportunity to grow your career in a mission-driven company, surrounded by passionate colleagues.

Here's what we offer:

• Flexible holidays policy : Take the holidays you need, while coordinating with your team and respecting the demands of your role.
• Health insurance with Alan for you and your family.
• Reimbursement if you come to the office by public transport.
• Team incentive bonus : Based on your total salary package.
• Flexible remote work : You can work remotely 2 days per week, with flexibility, provided you coordinate with your colleagues. Company events and travels : Join quarterly company events and visit our three offices

Soil Capital is an equal opportunity employer. We encourage applications from all candidates who meet the job requirements, regardless of their race, colour, religion, sex, sexual orientation, age, or disability.

Our hiring process

In order to find the perfect match, we have set up a comprehensive hiring process to give you the opportunity to get to know all the key contributors to the role. Between each step, you'll always receive feedback:

• People interview (30 min) with Charlotte, Talent Acquisition Specialist, to get to know you more

• First interview (45 min) with Auxi (Lead Data Collection) to go much more in depth into the role

• Technical interview (1 hour) to evaluate the technical aspects with Jelle (Data Team Lead) & Victor (Impact Researcher) - you will receive more details during the interviews

• Last step interview (30 min) with Guillaume, COO

Be part of a supportive, dynamic team that celebrates successes together and works toward a shared mission of transforming the future of agriculture!

How to Submit an Application:

After reading and knowing the criteria and minimum requirements for qualifications that have been explained from the Data Scientist job info - Soil Capital Remote in Louvain-la-Neuve above, thus jobseekers who feel they have not met the requirements including education, age, etc. and really feel interested in the latest job vacancies Data Scientist job info - Soil Capital Remote in Louvain-la-Neuve in 2025-04-30 above, should as soon as possible complete and compile a job application file such as a job application letter, CV or curriculum vitae, FC diploma and transcripts and other supplements as described above, in order to register and take part in the admission selection for new employees in the company referred to, sent via form this bottom.