Data Scientist - Agronomy
Doriane is a leading AgriTech company specializing in software solutions for agronomic R&D and innovation. Our SaaS platform Bloomeo is used by major agricultural players worldwide — seed companies, biosolution leaders, technical institutes, cooperatives, and research organizations.
We help our clients make better decisions by turning complex agronomic data into actionable knowledge. Our work directly supports a major transition in agriculture: reducing reliance on chemical inputs while maintaining crop performance and yields in the context of climate change.
The role
We are looking for a Data Scientist with a strong interest in agronomy.
You will work at the intersection of data science, agronomy and product, contributing both to the evolution of Bloomeo and to collaborative R&D projects involving clients, universities and research institutes.
This role offers a high level of autonomy, close interaction with domain experts, and the opportunity to see your work directly used in real-world decision-making.
Your missions
You will contribute to several strategic data science topics, including:
At Doriane, this is not a generic data science position focused on abstract datasets or disconnected models.
We help our clients make better decisions by turning complex agronomic data into actionable knowledge. Our work directly supports a major transition in agriculture: reducing reliance on chemical inputs while maintaining crop performance and yields in the context of climate change.
The role
We are looking for a Data Scientist with a strong interest in agronomy.
You will work at the intersection of data science, agronomy and product, contributing both to the evolution of Bloomeo and to collaborative R&D projects involving clients, universities and research institutes.
This role offers a high level of autonomy, close interaction with domain experts, and the opportunity to see your work directly used in real-world decision-making.
Your missions
You will contribute to several strategic data science topics, including:
- Envirotyping & agronomic contextualization Model and integrate pedo-climatic, environmental and agronomic context to better explain variability in field trial results.
- Data quality & anomaly detection Design robust methods to detect inconsistencies, outliers and anomalies in complex agronomic datasets.
- Statistics embedded in the product Formalize and implement statistical methods that can be directly integrated into Bloomeo and used by agronomists and R&D teams.
- Predictive modeling of plant behavior Develop models to predict crop or plant responses to environmental conditions, agronomic practices or genetic material.
- Generative AI & semantic harmonization Apply NLP and generative AI techniques to reconcile heterogeneous field observations expressed with different vocabularies but referring to the same agronomic concepts.
- Collaboration & knowledge sharing Work closely with Doriane’s product, software engineering and agronomy teams, and interact regularly with clients, academic partners and collaborative project consortia.
At Doriane, this is not a generic data science position focused on abstract datasets or disconnected models.
- You work on real agronomic data, coming from field trials, crops, soils, climate and agricultural practices — data that is complex, noisy and highly contextual.
- Your models are not proofs of concept: they are designed to be integrated into Bloomeo, a production software used daily by agronomists, researchers and R&D teams worldwide.
- You collaborate closely with agronomists, software engineers and product teams, as well as with clients, universities and research institutes involved in collaborative projects.
- You contribute to structuring agronomic knowledge, using statistics, machine learning and generative AI to bridge gaps between heterogeneous observations and vocabularies.
- Your work directly supports a major transition in agriculture: reducing chemical inputs while maintaining yields and performance despite climate change.
- You apply data science to high-impact, real-world decisions, where scientific rigor and operational usability matter as much as model performance.
- Degree in data science, statistics, engineering, agronomy or a closely related field
- Strong interest in agronomy is essential Prior experience in agriculture, agronomic research, plant science, environmental or agri-food data is a strong advantage
- Solid foundations in statistics and machine learning
- Proven ability to work with Python and common data science libraries (pandas, NumPy, scikit-learn, etc.)
- Comfortable with complex, heterogeneous datasets (field trials, observations, sensors, spatial or temporal data)
- Curious, rigorous, and able to translate real-world agronomic questions into data-driven approaches
- Enjoys collaborative work in multidisciplinary and international environments
- Fluent technical English is mandatory (international clients and projects), even if most internal interactions are in French
- Work on meaningful agronomic challenges with tangible impact
- Contribute to a market-leading product used by major agricultural players worldwide
- Be part of a company deeply involved in collaborative and research-driven projects
- Combine data science, agronomy and purpose in a single role
- Join a growing, human-scale company based in Nice, with strong scientific and technical ambitions
- First interview with Louis Gauthier, Co-Managing Director of Doriane (remote).
- Second interview with Tristan Duminil, Head of Agronomy (remote).
- Final round in Nice, including meetings with several members of the Doriane team: a future teammate (Djampa), the CTO (Florian), the COO (Pascal), and the Co-Managing Director (Marine). The final round is also an opportunity to discover Doriane’s working environment, meet the team, and get a concrete feel for how we collaborate on a daily basis.