Data Scientist – Agronomy

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 Dorianes 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.