Job Description
SENIOR ANALYST – DATA (INTERNAL ADVERT)
THE ORGANIZATION
The
Alliance of Bioversity International and the International Center for Tropical
Agriculture (CIAT) delivers research-based solutions that harness agricultural
biodiversity and sustainably transform food systems to improve people’s lives.
Alliance solutions address the global crises of malnutrition, climate change,
biodiversity loss, and environmental degradation. With novel partnerships, the
Alliance generates evidence and mainstreams innovations to transform food
systems and landscapes so that they sustain the planet, drive prosperity, and
nourish people in a climate crisis. The Alliance is part of CGIAR, a global
research partnership for a food-secure future. Please visit http://www.alliancebioversityciat.org/for more
information on the Alliance.
The
International Institute of Tropical Agriculture (IITA) is a not-for-profit
institution that generates agricultural innovations to meet Africa’s most
pressing challenges of hunger, malnutrition, poverty, and natural resource
degradation. Working with various partners across sub-Saharan Africa, we
improve livelihoods, enhance food and nutrition security, increase employment,
and preserve natural resource integrity. IITA is a member of CGIAR, a global
agriculture research partnership for a food secure future. Please visit http://www.iita.org/for more information on IITA.
ABOUT THE POSITION
The Senior
Analyst Data role is established to provide hands-on technical support for
agronomic data management, analytics, and modelling to advance data-driven
decision support tools and nutrient management research. The post holder will
curate and standardize agronomic datasets, develop analytical and machine
learning workflows, generate spatial and temporal crop insights, and support
technical reporting, scientific publications, and stakeholder engagement. The
role ensures that data, analytical methods, and modelling outputs are well
managed, aligned with project objectives, and effectively translated into
robust evidence for digital agronomy tools and research outcomes.
MAIN DUTIES AND RESPONSIBILITIES INCLUDE:
AGRONOMIC DATA MANAGEMENT
The Senior Analyst will support the implementation of agronomic data management,
analytics, and modelling activities across multiple projects, countries, and
partners. The role requires close collaboration with scientists, data managers,
software developers, and external partners to deliver high-quality data
products, machine learning models, and decision-support tools.
The role will
involve:
Curate, standardize, and
manage agronomic and survey datasets using CAROB R-based workflows and FAIR
data standards.Develop and implement
analytical workflows in R for data processing, integration, augmentation, and
analysis to support nutrient management research.Train, validate, and apply
machine learning models to generate hyperlocal fertilizer recommendations and
support digital agronomy tools.Develop and apply
process-based and machine learning models for spatial and temporal crop yield
prediction and agronomic decision support.Conduct statistical,
geospatial, and integrated analyses of agronomic, soil, climate, and survey
datasets to generate actionable insights.Support technical meetings,
workshops, and consultations by communicating analytical methods and modelling
approaches to multidisciplinary teams and partners.Prepare technical reports,
research documentation, and scientific publications to disseminate project
findings.Provide technical and
analytical support to deliver project objectives and strengthen data-driven
agronomic research.Maintain comprehensive
documentation of datasets, scripts, analytical workflows, specifications, and
data access procedures to ensure reproducibility and knowledge sharing.
AGRONOMIC DATA ANALYTICS AND MODELLING
The Senior Analyst will support agronomic data
analytics and modelling, collaborating with internal and external stakeholders
to support the development of evidence-based decision-support tools and
research outputs.
The role
will:
Collaborate with scientists,
data managers, software developers, and project teams to deliver high-quality
analytical and modelling outputs.Engage with national and
international research partners to support data sharing, harmonization, and
implementation of FAIR data standards.Provide technical guidance on
data management, analytical workflows, machine learning, and crop modelling
approaches.Support technical meetings,
workshops, and consultations by presenting analytical methods, modelling
results, and research findings.Contribute technical inputs
to multidisciplinary research activities and digital agronomy initiatives.Liaise with collaborators to
facilitate access to agronomic, soil, climate, and survey datasets required for
project implementation.Support the integration of
analytical outputs into digital decision-support tools and research products.Contribute to scientific
publications, technical reports, and knowledge-sharing activities with project
partners and stakeholders.
AGRONOMIC DATA ANALYTICS AND DECISION SUPPORT
The Senior
Analyst will support the delivery of high-quality agronomic
data management, analytics, modelling, and decision-support products that
strengthen digital agronomy research and evidence-based nutrient management.
The role will:
Deliver high-quality, FAIR-compliant agronomic datasets
using standardized CAROB R-based workflows and data standards.Develop and maintain robust R analytical pipelines for
processing, integrating, and analysing agronomic, soil, climate, and survey
data. Produce validated machine learning and process-based modelling outputs to
support hyperlocal fertilizer recommendations and crop yield prediction.Generate statistical, geospatial, and data-driven insights
that inform site-specific nutrient management and digital decision-support
tools.Contribute technical inputs to project meetings, workshops,
and stakeholder engagements, communicating analytical methods and modelling
results.Prepare technical reports, research documentation, and
scientific publications that disseminate analytical findings and project
outcomes.Provide timely technical and analytical support to ensure
successful delivery of project objectives and milestones.Maintain comprehensive documentation of datasets, scripts,
analytical workflows, and metadata to ensure reproducibility, transparency, and
long-term usability of project outputs.
REQUIREMENTS:
EDUCATION
Bachelor's degree in Agronomy, Crop Science, Agricultural
Engineering, Agricultural Data Science, Statistics, Computer Science,
Geoinformatics, Environmental Science, or a related field..
EXPERIENCE
At least 5 years of
relevant experience in agronomic data analysis, agricultural research, or data
management.Demonstrated experience using R (or similar statistical programming languages) for data processing,
analysis, and visualization.Experience working with
agronomic, soil, climate, survey, or spatial datasets.Experience applying
statistical methods and, preferably, machine learning techniques to
agricultural datasets.Familiarity with geospatial
analysis and GIS tools (e.g., QGIS, ArcGIS, or R spatial packages).Experience supporting crop
modelling or agricultural decision-support systems is an added advantage.Experience preparing
technical reports, documentation, and scientific outputs.Experience working in
multidisciplinary research teams and collaborating with national and
international partners.Demonstrated ability to
manage multiple tasks, maintain well-documented analytical workflows, and
deliver high-quality outputs within agreed timelines.
TECHNICAL COMPETENCIES
Proficiency in R for data management, statistical
analysis, and visualization.Good understanding of agronomy, crop production systems, and
nutrient management principles.Knowledge of statistical analysis, data quality assurance,
and data management best practices.Familiarity with machine learning methods and their
application to agricultural datasets.Experience with geospatial analysis and GIS tools (e.g.,
QGIS, ArcGIS, or R spatial packages).Basic understanding of crop simulation models (e.g., APSIM,
DSSAT) is an added advantage. Strong analytical, problem-solving, and
quantitative reasoning skills.Ability to manage multiple tasks, prioritize work, and meet
deadlines.Excellent documentation, technical writing, and reporting
skills.Strong communication and interpersonal skills, with the
ability to work effectively in multidisciplinary and multicultural teams.High level of attention to detail and commitment to
producing high-quality, reproducible analytical outputs.Ability to work independently while contributing effectively
within a collaborative research environment.Proficiency in written and spoken English is required.
Knowledge of version control
tools (e.g., Git/GitHub) and FAIR data principles is an added advantage.
EXPECTED DELIVERABLES
FAIR-compliant agronomic,
survey, soil, and climate datasets curated, standardized, and documented using
CAROB R-based workflows.Reproducible R scripts and
analytical workflows for data processing, quality control, integration, and
statistical analysis.Validated machine learning
models and hyperlocal fertilizer recommendation products supporting digital
agronomy and decision-support tools.Spatial and temporal crop
yield prediction outputs generated using process-based and machine learning
models.Statistical, geospatial, and
integrated analyses completed to support site-specific nutrient management and
agronomic research.Technical documentation,
metadata, and workflow specifications maintained to ensure reproducibility and
adherence to FAIR principles.Technical reports, analytical
summaries, and presentations produced to communicate modelling results and
research findings.Scientific manuscripts,
conference abstracts, and other research outputs prepared in collaboration with
project teams.Technical contributions
provided to project meetings, workshops, stakeholder consultations, and digital
agronomy initiatives.High-quality analytical outputs delivered on time,
supporting project milestones, decision-support tool development, and
evidence-based agronomic research.
KEY PERFORMANCE MILESTONES
FAIR-compliant agronomic and survey datasets curated,
standardized, and documented using CAROB R-based workflows.Reproducible R analytical pipelines for data processing,
quality control, integration, and statistical analysis.Validated machine learning models and hyperlocal fertilizer
recommendation outputs for digital decision-support tools.Spatial and temporal crop yield prediction outputs generated
using process-based and machine learning models.Statistical, geospatial, and integrated analyses of
agronomic, soil, climate, and survey datasets to support nutrient management
research.Technical reports, analytical summaries, and documentation
that communicate project findings and modelling results.Scientific manuscripts, conference presentations, and other
research outputs contributing to project dissemination.Well-documented scripts, workflows, metadata, and technical
specifications to ensure reproducibility and compliance with FAIR principles.Technical inputs provided to project meetings, workshops,
and stakeholder consultations to support evidence-based decision making.Timely delivery of high-quality analytical outputs that
contribute to project milestones, digital agronomy tools, and research
objectives.
EVALUATION CRITERIA
Relevance and quality of
academic qualifications in agronomy, agricultural data science, statistics,
computer science, or a related field.Demonstrated experience in
agronomic data management, statistical analysis, and data curation.Proficiency in R (or
equivalent statistical programming languages) for data processing, analysis,
and visualization.Experience applying machine
learning and/or crop modelling approaches to agricultural research.Experience working with
agronomic, soil, climate, survey, and geospatial datasets.Demonstrated ability to
develop reproducible analytical workflows and maintain high-quality technical
documentation.Quality of technical writing,
reporting, and contribution to scientific publications or research outputs.Ability to interpret
analytical results and communicate technical findings to multidisciplinary
teams.Evidence of effective
collaboration in multidisciplinary and multicultural research environments.Strong analytical,
problem-solving, organizational, and time management skills.Proficiency in written and
spoken English. Knowledge of French is an added advantage.
TERMS OF EMPLOYMENT
This is a
nationally recruited position based at IITA Nairobi, Kenya. The
initial contract will be for one and half yearssubject
to a probation period of three months
and is renewable depending on performance and availability of resources.
This
position is graded at BG07 level, with a minimum basic salary of KES 227,931.00
in a scale of BG01 to BG14 (BG14 being the highest level according to the
Alliance job classification framework policy). We offer a competitive salary
and excellent benefits including but not limited to insurance, retirement plan,
staff training and development, paid time off and flexible working
arrangements.
The
Alliance Bioversity-CIAT is committed to fair, safe, and inclusive workplaces.
We believe that diversity powers our innovation, contributes to our excellence,
and is critical for our mission. Recruiting and mentoring staff to create an
inclusive organization that reflects our global character is a priority. We
encourage applicants from all cultures, races, colors, religions, sexes,
national or regional origins, ages, disability statuses, sexual orientations,
marital status, and gender identities. Female candidates are strongly
encouraged to apply.
APPLICATIONS
Applicants
are invited to visit https://www.bioversityinternational.org/jobs/to get full details of the position and to submit their applications.
Applications MUST include reference number Ref: ( RFP301374 )- SENIOR ANALYST- DATA the position applied for. Application and CV should be saved as one
document using the candidate’s lastname, firstname for ease of sorting.
Note: The
Alliance does not charge a fee at any stage of the recruitment process
(application, interview meeting, processing or training). The Alliance also
does not concern itself with information on applicants' bank accounts.
Applications closing date:27th July 2026