Data Scientist jobs in France

Reports to: Research Team Leader - Soils, Waters and Agronomy. Location: Abu Dhabi, UAE.

ICARDA is working towards developing a climate‑resilient and digitally advanced agrifood sector for the global drylands.

Its areas of focus encompass agronomy, climate, crop improvement, socioeconomics, small ruminants, soil, and water challenges, employing methods such as situ observations, experiments, process modeling, stakeholder engagement, and a suite of digital initiatives under CGIAR.

This position is ideal for a Data Scientist with expertise in Predictive or Generative AI, Machine Learning, Applied Statistics, or Systems Modeling. It is designed to work in close coordination with the GeoAgro Research Team, complementing its leadership in climate change science, geospatial analysis, and digital agriculture innovation.

As ICARDA advances integrated AI solutions that draw on geospatial analytics, machine learning, crop and soil modeling, and diverse data streams, this role ensures strong collaboration across research teams—particularly with GeoAgro, which leads ICARDA’s Cross‑Cutting Research Theme on Climate‑Smart Predictive Agriculture.

The International Center for Agricultural Research in the Dry Areas (ICARDA) is a treaty‑based international non‑profit research organization supported by CGIAR. ICARDA’s mission is to reduce poverty, enhance food, water, and nutritional security, as well as environmental health in the face of global challenges including climate change.

We do this through innovative science, strategic partnerships, linking research to development, and capacity development that takes into account gender equality and the role of youth in transforming the dry areas. ICARDA works in partnership with governments, universities, civil society, national agricultural research organizations, other CGIAR Research Centers, and the private sector.

\>With its temporary Headquarters in Beirut, Lebanon, ICARDA operates in regional and country offices across Africa, Asia, and the Middle East. For more information: www.icarda.org.

• Work across various ICARDA programs with a cohort of datasets (geospatial, biophysical, climatic, genomic, and socioeconomic) to improve predictive capabilities of various agrifood system processes (from gene to regional scales).
• Develop Predictive AI solutions (machine learning, ANN, big data‑based forecasting) and use generative AI applications to accelerate resilience in agriculture in the non‑tropical drylands where ICARDA operates.
• Examples of work include mapping crop yield gaps, crop‑water relations, soil salinity, climate risks, crop and livestock disease outbreaks, pest infestations, crop ideotype design, analyzing HTP phenotypic data, mapping soil carbon, and socioeconomic processes.
• Utilize geospatial analysis and remote sensing to assess dynamics of land use, crop conditions, and natural resources in irrigated, rainfed, deserts and rangelands; conduct TPE analytics to help crop improvement.
• Take leadership in cloud‑based Data/AI workflows using AWS, Azure, or GCP along with the necessary cyber security protocols.
• Provide thought leadership and advocacy for the application of different Large Language Models (LLMs) and GPTs for agricultural applications, such as text analysis of agricultural reports and farmer interviews. Provide supervision and oversight to test the efficacy of the LLMs/GPTs developed in CGIAR and bilateral initiatives for e‑extension service platforms and other tools.
• Engage in science‑policy dialogues on digital actions with key stakeholders at national and sub‑national levels and liaise with key partners and play an active role in resource mobilization of the digital and data‑driven research program at ICARDA.
• Develop user‑friendly applications and dashboards to visualise and communicate data insights to stakeholders in collaboration with developers and the software industry.
• Be the focal point for ICARDA to identify, collect, and curate relevant data from various ICARDA teams, external sources including government agencies, farmers, and remote sensing platforms complying with the CGIAR FAIR data (Findable, Accessible, Interoperable, Reusable) principles.
• Explore the use of IoT devices and sensors for data collection and real‑time monitoring of agricultural and hydrometeorological variables and archive it to centralized databases located within ICARDA IT platforms.
• Lead and support concept note and proposal development to strengthen ICARDA’s resource mobilization efforts, while advancing a vibrant Digital and Data Science portfolio through collaborative project design and strategic partnerships.
• Stay updated on the latest advancements in the field and explore their potential applications in the non‑tropical dryland regions and liaise with key partners and stakeholders.
• Publish research findings in peer‑reviewed journals and conferences.
• Strengthen institutional capacity in data science and AI through training, mentoring junior staff, embedding reproducible workflows, and promoting standardized practices across projects.

This is an internationally recruited staff position for which ICARDA offers an attractive compensation package including a competitive salary, medical insurance, 30 days of annual leave, five months’ maternity leave, and 15 days’ paternity leave. The successful candidate will be offered an initial contract of 3 years, renewable subject to continued need for the position, availability of funds and satisfactory performance. The first year will be a probationary period. ICARDA accepts applications only in English, which is the organization’s official communication language. Applications in other languages will not be considered. Only shortlisted applications will be contacted.

• Ph.D. in a field closely related to agriculture with strong quantitative skills (such as Data Science, Machine Learning, Computer Science, Applied Statistics, Agriculture, Biological Science, or Earth Science), or a related discipline.
• A minimum of 10 years of experience for Scientist level or 10 years for Senior Scientist level is required.
• Candidates with a Master’s degree in the above‑mentioned fields should have at least 12 years of relevant experience deploying AI and data solutions in real‑world projects and industries.
• Experience in leading teams on topics such as Artificial Neural Networks (ANN), machine learning‑based data analysis, process modeling, geospatial analysis, and remote sensing is essential.
• Familiarity with related software, including ArcGIS, QGIS, Google Earth Engine (GEE), and GDAL, is advantageous.
• Proficiency in cloud computing platforms such as Google Colab, AWS, Azure, and GCP is desirable, along with knowledge of database management systems (e.g., SQL, PostgreSQL, NoSQL).
• Demonstrated ability to lead data science projects and teams effectively.
• Excellent communication and interpersonal skills are essential for engaging and collaborating with diverse stakeholders.
• Proficiency in facilitating science‑policy dialogues and advocating for digital transformation in public forums is frequently required.
• Capable of working both independently and collaboratively within a team setting.
• Previous experience in agricultural research or related fields.
• Knowledge of the agricultural context in the dryland regions.
• Experience with leading ICT4D and data‑centric projects.
• Track record of publications in relevant scientific journals and web‑based repositories such as GitHub.

• Strong programming skills in languages such as Python, R, and JavaScript to develop and implement AI and ML solutions.