Join Our Whatsapp channel - CLICK HERE

Research Assistant

Role Purpose

The Research Assistant is responsible for supporting the collection, management, analysis, and interpretation of climate, weather, soil, and agricultural data to advance research and data-driven decision-making. The role contributes to the development and maintenance of digital data platforms, supports the validation of climate and weather forecast products, and assists in developing automated data processing workflows.

Working closely with researchers, data scientists, software developers, and national partners, the Research Assistant applies data science, geospatial analysis, and programming skills to improve the quality, accessibility, and reliability of environmental and agricultural datasets while supporting collaborative research initiatives.

Key Responsibilities

1. Data Collection and Management

The Research Assistant supports the acquisition, organization, and maintenance of research datasets.

Key responsibilities include:

• Collect, ingest, clean, and manage weather, climate, soil, agricultural, and environmental datasets.

• Verify data accuracy, completeness, and consistency before analysis.

• Organize datasets for research, reporting, and operational use.

• Maintain data repositories and ensure proper documentation of datasets.

• Monitor data quality and resolve inconsistencies where necessary.

• Support the integration of data from multiple internal and external sources.

2. Climate and Environmental Data Analysis

The role assists in the analysis of climate and environmental information to support research activities.

Responsibilities include:

• Analyze climate variables such as rainfall, temperature, humidity, and seasonal forecasts.

• Support statistical analysis of environmental and agricultural datasets.

• Assist in identifying trends, anomalies, and patterns within climate data.

• Prepare analytical summaries and visualizations for research outputs.

• Contribute to the interpretation of research findings.

• Support evidence-based recommendations for project activities.

3. Research Systems and Platform Development

The Research Assistant contributes to the development and maintenance of digital research platforms.

Responsibilities include:

• Support the development and maintenance of platforms such as AgDataHub.

• Assist in improving system functionality and data accessibility.

• Maintain research databases and digital repositories.

• Support testing and deployment of new platform features.

• Ensure research platforms remain reliable, secure, and user-friendly.

• Document system updates and technical improvements.

4. Forecast Validation and Quality Assurance

The role supports quality assurance activities for climate and forecast products.

Responsibilities include:

• Assist in benchmarking climate and weather forecast products.

• Validate forecast outputs using historical and observational datasets.

• Compare forecast performance against established standards.

• Identify discrepancies and recommend improvements.

• Prepare validation reports and performance summaries.

• Support continuous improvement of forecasting methodologies.

5. Programming and Workflow Automation

The Research Assistant develops automated tools that improve research efficiency.

Responsibilities include:

• Develop and maintain Python scripts for data processing and analysis.

• Automate repetitive research workflows where appropriate.

• Optimize data processing pipelines for efficiency and scalability.

• Maintain version-controlled code repositories using Git and GitHub.

• Troubleshoot technical issues affecting research workflows.

• Document scripts and technical procedures for future reference.

6. Collaboration and Stakeholder Engagement

The role works closely with internal and external stakeholders to support research activities.

Responsibilities include:

• Collaborate with researchers, software developers, and data scientists on multidisciplinary projects.

• Liaise with national meteorological agencies, research institutions, and project partners.

• Support data-sharing and collaborative research initiatives.

• Participate in technical meetings, workshops, and project discussions.

• Provide technical support to research teams where required.

• Promote effective communication between project stakeholders.

7. Research Support and Reporting

The Research Assistant contributes to the preparation of research outputs and project documentation.

Responsibilities include:

• Prepare technical reports, research summaries, and analytical documentation.

• Support the preparation of presentations and scientific publications.

• Maintain accurate research records and documentation.

• Assist in monitoring project milestones and deliverables.

• Contribute to grant reporting and project evaluations where required.

• Perform other research-related duties assigned by project leadership.

Academic Qualifications

Applicants should possess:

• Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Geospatial Science, Information Technology, or another related discipline from a recognized institution.

• Professional certifications in Python Programming, Cloud Computing, Data Engineering, GIS, Machine Learning, or related technical fields will be an added advantage.

Required Experience

The ideal candidate should demonstrate:

• A minimum of two (2) years of relevant professional or research experience in data science, climate analytics, geospatial analysis, or a related technical field.

• Strong proficiency in Python for data processing, automation, and analysis.

• Practical experience using Git and GitHub for version control and collaborative software development.

• Experience working in Linux/Unix environments and using command-line tools.

• Experience applying deep learning techniques, including Convolutional Neural Networks (CNNs), to geospatial or remote sensing datasets.

• Familiarity with cloud computing platforms, particularly Amazon Web Services (AWS).

• Experience working with distributed data systems such as Apache Druid or similar technologies will be an added advantage.

• Experience managing large environmental, agricultural, or climate datasets is desirable.

• Knowledge of French will be an added advantage.

Key Competencies and Personal Attributes

Technical Competencies

• Climate and environmental data analysis.

• Python programming and workflow automation.

• Data cleaning, validation, and management.

• Statistical analysis and data visualization.

• Git and GitHub version control.

• Linux/Unix operating environments.

• Cloud computing using AWS.

• Machine learning and deep learning applications.

• Geospatial and remote sensing data analysis.

• Database and distributed data management.

Analytical and Research Skills

• Strong analytical and problem-solving abilities.

• Excellent quantitative and statistical skills.

• Ability to interpret complex datasets and generate actionable insights.

• Strong research methodology and documentation skills.

• Attention to detail and commitment to data quality.

Communication and Collaboration

• Excellent written and verbal communication skills in English.

• Ability to explain technical concepts to multidisciplinary audiences.

• Strong teamwork and stakeholder engagement skills.

• Ability to collaborate effectively with researchers, developers, and institutional partners.

• Good presentation and report-writing skills.

Personal Attributes

• High level of integrity and professionalism.

• Curious, innovative, and committed to continuous learning.

• Self-motivated with the ability to work independently and collaboratively.

• Strong organizational and time-management skills.

• Adaptable and capable of working in dynamic research environments.

• Results-oriented with a commitment to delivering high-quality research outputs.

Application

Go to International Livestock Research Institute (ILRI) on www.ilri.org to apply