IRS23158 Data Science Specialist
CIMMYT, Kenya
Job Description
CIMMYT is a cutting-edge, non-profit, international organization dedicated to solving tomorrow’s problems today. It is entrusted with fostering improved quantity, quality, and dependability of production systems and basic cereals such as maize, wheat, triticale, sorghum, millets, and associated crops through applied agricultural science, particularly in the Global South, through building strong partnerships. This combination enhances the livelihood trajectories and resilience of millions of resource-poor farmers, while working towards a more productive, inclusive, and resilient agrifood system within planetary boundaries.
CIMMYT is a core CGIAR Research Center, a global research partnership for a food-secure future, dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources.
For more information, visit cimmyt.org.
The Breeding Modernization and Innovation (BMI) Program at CIMMYT works with CGIAR and NARES breeding teams to develop better-performing, farmer-preferred crop varieties and to reduce the area weighted average age of varieties in farmers’ fields, providing real-time adaptation to climate change, evolving markets, and production systems.
As part of the BMI team, the Data Science Specialist will support the ACCELERATE work package to achieve the goals of optimizing breeding schemes, and improving data quality standards and analytics with CGIAR-NARES partners. This position will report to the Quantitative Genetics Lead, who is also the ACCELERATE Lead of Accelerated Breeding Initiative and will collaborate with CGIAR Biometricians and Quantitative Geneticists and the Breeding Resources Initiative team, including their Breeding IT, Lab Services, and Trailing and Nursery Teams.
The Data Science Specialist will support the CGIAR-NARES Biometrics and quantitative genetics team to set up and manage shared cloud computing resources for breeding analytics, co-develop analytical modules for the breeding data analytics semi-automated pipeline as well as develop CGIAR-NARES capacity on data quality standards and analytics. The successful candidate will have a strong background and experience in programming, cloud computing systems for agricultural research, and a deep understanding of statistics and biometrics.
The position will be based at CIMMYT-Nairobi Campus in Kenya or any other agreed-upon location within Africa and will involve significant international travel.
Specific duties:
- Developing analytical tools (e.g., software packages, web applications) to enhance the efficiency of agricultural research in collaboration with partner scientists.
- Assist the Genetic Innovation Breeding Analytics core team in improving data quality and standardizing analytics pipeline.
- Engaging with member breeding teams to create awareness of new tools and approaches for improving data quality standards and robust analyses in breeding pipelines.
- Developing strategy in collaboration with breeders and developing plans for the use of new analytics tools and methodologies.
- Mentoring and consulting with the partner breeding community.
- Contribute to the development of a training strategy and materials for implementation.
- Leading and contributing to both, virtual and hands-on training, and mentorship activities targeted at member breeding teams in Africa, Asia, and Latin America.
- Providing support to internal and external reviews and evaluations.
- Contributing to publications derived from the breeding optimization projects.
Requirements
- Ph.D. with 2 years’ experience or MSc with 7 years’ experience or BSc with 12 years’ experience in Computer Engineering, Data Science, or any other related field with an excellent and clear track record of international collaboration and providing Data Science support to multi-cultural teams, preferably in CGIAR-NARES settings. Experience working in Africa is highly recommended.
- In-depth understanding of practical breeding applications and logistical constraints relevant to breeding programs targeting the developing world (i.e., CGIAR centers, national systems, and private sector organizations).
- In-depth understanding of programming languages, web applications such as AWS, Posit Work Bench, among others.
- Expertise in statistical analysis software (R, mixed modeling, perhaps machine learning, etc.) and a creative and innovative mindset.
- A good understanding of quantitative genetics and underlying mathematical theory.
- Good reporting and communication skills in English (working language).
- The selected candidate must exhibit the following competencies: Problem-solving and decision-making, client orientation, negotiation and conflict resolution, communication, and teamwork.
Benefits
The position is for an initial fixed term of