Job Description
The Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF) is inviting applications for the position of Associate Scientist-Data Analyst based in Nairobi, Kenya. This opportunity is ideal for a highly analytical professional who enjoys transforming complex scientific data into meaningful insights that support agricultural innovation and sustainable development. The successful candidate will work closely with multidisciplinary research teams supporting initiatives delivered in collaboration with ICRISAT and other international research partners dedicated to strengthening food systems, improving rural livelihoods, and enhancing environmental resilience across Africa and beyond.
The Associate Scientist – Data Analyst will contribute to the planning, execution, and evaluation of agricultural research activities by applying advanced statistical methods, data management practices, and modern analytical techniques. The role requires an individual who is comfortable working with large and diverse datasets generated from field experiments, laboratory studies, and collaborative research program. By ensuring that research data are accurate, well organized, and scientifically reliable, the successful candidate will play an important role in improving the quality and impact of research outputs.
Working within an international scientific environment, the successful applicant will collaborate with statisticians, agronomists, crop scientists, economists, environmental specialists, and digital agriculture experts. The position involves supporting experimental design, preparing randomized field trial layouts, developing analytical workflows, producing visual reports, and interpreting research findings that guide evidence-based decision-making. The successful candidate will also assist researchers in identifying suitable statistical approaches for different experimental conditions while maintaining high standards of scientific integrity.
The position offers an opportunity to utilize programming languages and analytical software to automate data processing, improve research efficiency, and strengthen reproducibility across research projects. The successful candidate will contribute to developing and enhancing analytical scripts that improve data quality, generate informative visualizations, and simplify reporting processes for researchers and project partners.
Beyond technical responsibilities, the Associate Scientist – Data Analyst will actively participate in preparing scientific publications, technical reports, conference presentations, and knowledge products that communicate research findings to diverse audiences. The role also includes supporting training initiatives by building the statistical and data management capacity of scientists, research assistants, and collaborating institutions.
This position requires excellent communication skills, intellectual curiosity, and the ability to work effectively within multicultural teams operating across several countries. Candidates should demonstrate sound judgement, initiative, attention to detail, and the flexibility to manage multiple assignments while meeting project timelines.
CIFOR-ICRAF offers a collaborative and inclusive workplace where innovation, scientific excellence, and professional growth are encouraged. Employees benefit from exposure to internationally recognized research program addressing global challenges related to agriculture, climate resilience, biodiversity conservation, and sustainable land management. If you are passionate about applying advanced data science to improve agricultural research and create lasting development impact, this position offers an outstanding opportunity to contribute to meaningful scientific discoveries while advancing your professional career.
Key Responsibilities
- Design statistically sound experimental layouts for agricultural field trials and research studies.
- Prepare randomized treatment allocations using recognized experimental design methodologies.
- Support scientists throughout research projects by providing statistical guidance during planning, implementation, and reporting stages.
- Develop efficient workflows for collecting, validating, cleaning, organizing, and documenting research datasets.
- Perform descriptive, inferential, multivariate, and advanced statistical analyses using appropriate methodologies.
- Produce high-quality charts, dashboards, statistical summaries, and visualizations that clearly communicate research findings.
- Develop, optimize, maintain, and document analytical scripts using R programming language.
- Apply Python programming techniques to automate repetitive data processing tasks and improve analytical efficiency.
- Utilize SAS and other statistical software where appropriate for specialized analytical requirements.
- Ensure research datasets comply with institutional standards for quality assurance, consistency, traceability, and reproducibility.
- Collaborate closely with multidisciplinary researchers to interpret statistical outputs and explain analytical findings.
- Support predictive modelling, trend analysis, simulation studies, and quantitative decision-support tools.
- Review research protocols to ensure statistical validity before implementation.
- Participate in preparing scientific manuscripts for publication in peer-reviewed journals.
- Contribute statistical content to technical reports, donor reports, policy briefs, and project documentation.
- Assist with the preparation of conference presentations, posters, and scientific communication materials.
- Support data governance practices including secure storage, version control, metadata management, and documentation.
- Provide statistical consultation to research teams working across multiple agricultural disciplines.
- Organize and facilitate internal workshops covering statistical methods, data visualization, and analytical software.
- Mentor junior researchers and technical staff on best practices in research data management.
- Maintain awareness of emerging analytical technologies and recommend improvements were beneficial.
- Collaborate effectively with international partners across different countries and research institutions.
- Monitor project milestones and deliver analytical outputs within agreed timelines.
- Uphold research ethics, confidentiality, and institutional data protection standards.
- Prepare accurate documentation that enables reproducibility of statistical analyses.
- Participate in project meetings, technical discussions, and collaborative planning sessions.
- Troubleshoot analytical challenges by identifying practical, evidence-based solutions.
- Maintain organized records of analytical procedures and research outputs.
- Support continuous improvement initiatives that strengthen institutional research quality.
- Perform additional research-related responsibilities assigned by the supervising scientist consistent with organizational objectives.
Qualifications & Requirements
- PhD in Statistics, Biostatistics, Data Science, Applied Statistics, or a closely related quantitative discipline.
- Minimum three years of relevant professional experience supporting agricultural or scientific research.
- Demonstrated expertise in experimental design and statistical modelling.
- Strong proficiency in R programming for statistical computing and visualization.
- Practical experience using Python for data analysis and workflow automation.
- Working knowledge of SAS or comparable statistical software.
- Experience managing complex research datasets from multiple sources.
- Excellent understanding of data quality assurance and validation techniques.
- Knowledge of predictive analytics and advanced quantitative methodologies.
- Strong analytical thinking and evidence
- based problem
- solving abilities.
- Excellent written and verbal communication skills.
- Ability to explain statistical concepts to non
- statistical audiences.
- Experience contributing to scientific publications is advantageous.
- Strong organizational and time management abilities.
- Ability to work independently with minimal supervision.
- Excellent collaboration skills within multicultural and multidisciplinary environments.
- High attention to detail and commitment to research integrity.
- Proficiency in Microsoft Office and digital collaboration tools.
- Strong commitment to continuous professional learning.
- Fluency in English.
How to Apply
Interested candidates should submit their application through the official CIFOR-ICRAF online recruitment portal before the closing date. A complete application should include an updated curriculum vitae, a cover letter outlining relevant qualifications and experience, and any additional documents requested during the application process. Only shortlisted candidates will be contacted for the next stage of the recruitment process. Applicants are encouraged to submit their applications well before the deadline to allow sufficient time for processing.