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.

Why this role is different from a classic Data Scientist job

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.

Who we are looking for

• 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

Why join Doriane

• 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

The interview process is structured as follows:

• 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.