Data Specialist – Agronomic Analytics and Modeling

CIMMYT is looking for a:

Data Specialist – Agronomic Analytics and Modeling

This post will contribute to both bilateral projects requiring data analytics and ONECGIAR initiatives including Harnessing digital technologies (DX1) and AgriLAC Resiliente. This is a position within the MEAL team funded both by SAS project portfolio, as well as OneCGIAR initiatives and bilaterals in Asia (Bihar) and Africa (USAID).

Summary of responsibilities

1. Develop and implement best practices and protocols for data cleaning, analysis and modeling.
2. Design and oversee the development of complex statistical models for agronomic data analysis.
3. Implement machine learning and AI techniques to extract insights from large-scale agricultural datasets.
4. Validate and refine models to ensure accuracy and reliability of results.
5. Lead the development of methodologies for calculating key agricultural KPIs, including:

• Greenhouse Gas emissions
• Soil health indices
• Sustainable practice adoption rates

1. Ensure alignment of KPI calculations with international standards and best practices.
2. Collaborate with breeding data teams to integrate data-driven insights into agronomic analyses.
3. Implement data governance practices to ensure data integrity and security.
4. Oversee the development and maintenance of data pipelines and storage systems.
5. Prepare and present comprehensive reports on analytical findings to stakeholders
6. Develop data visualizations and dashboards to communicate complex information effectively
7. Collaborate with cross-functional teams to translate analytical insights into actionable recommendations.

Requirements

• Ph.D. in Data Science, Statistics, Computer Science, or a related field.
• Minimum 5 years of experience in leading data science teams, preferably in an agricultural or environmental context.
• Strong background in statistical analysis, machine learning, and predictive modeling.
• Proficiency in programming languages such as R, Python, and SQL.

Personal attributes and competencies

• Experience with big data technologies and cloud computing platforms.
• Demonstrated ability to translate complex analytical results into actionable insights.
• Excellent communication and leadership skills
• Knowledge of agricultural systems and environmental science is highly desirable.

Terms and conditions

• This is a Locally Recruited Staff (LRS) position and on competitive remuneration in local currency, commensurate with skills and experience.
• The appointment will be for a period of two (2) years, inclusive of a six-month probationary period, with the possibility of extension contingent upon performance, continued relevance of the position and available resources.
• The duty station will be in Nairobi, Kenya.