Readvertisement - Data Scientist

ICARDA; Montpellier; Sur place; EUR 55 000 - 75 000; Plein temps

Résumé du poste

A global research organization is seeking a Data Scientist to develop AI-driven solutions for agriculture. The role involves working with diverse datasets, leading innovative projects in predictive analytics, and collaborating across teams. Candidates should have a Ph.D. in a relevant field and at least 10 years of experience. Familiarity with AI methods and geospatial analysis is essential, along with strong programming skills. This position is located in Montpellier, France.

Qualifications

• Ph.D. in a field closely related to agriculture with strong quantitative skills.
• Minimum 10 years of experience for Scientist level.
• Experience in leading teams on data analysis, geospatial analysis, and remote sensing.

Responsabilités

• Develop Predictive AI solutions and conduct geospatial analysis.
• Collaborate with teams to enhance data-driven innovations.
• Provide leadership in cloud-based Data / AI workflows.

Connaissances

Data Science

Machine Learning

Applied Statistics

Geospatial Analysis

Programming in Python

Formation

Ph.D. in a relevant field

Master’s degree with 12 years of experience

Outils

ArcGIS

QGIS

AWS

Azure

Google Colab

Description du poste

Reports to

Research Team Leader - Soils, Waters and Agronomy

Location

Abu Dhabi, UAE

Main purpose of the position

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. This position 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 Data Scientist will be embedded within ICARDA’s institutional structure and will actively collaborate with biophysical modelers, geospatial scientists, climatologists, and other domain experts to co-develop data science–driven international public goods. This alignment fosters synergy, avoids duplication, and reinforces ICARDA’s capacity to deliver scalable, cross-program innovations for dryland resilience.

About ICARDA

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 : .

Main responsibilities

• Work across various ICARDA programs with a cohort of datasets : geospatial, biophysical, climatic, genomic and socioeconomic datasets 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.
• Example works include, but not limited to, 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 etc. Utilize geospatial analysis and remote sensing to assess dynamics of land use, crop conditions, and natural resources in irrigated, rainfed, deserts and rangelands, TPE analytics to help crop improvement etc.
• 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 the 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 visualize and communicate data insights to stakeholders in collaboration with developers and the software industry. These applications can be in across the ICARDA programs.
• 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 nontropical 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.

Requirements

Education, qualifications and experience

Essential qualifications and competencies

• 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 like Artificial Neural Networks (ANN), machine learning-based data analysis, and 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.

Desirable skills

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

Benefits