Data and Software Engineering Scientist

Role Overview

The Data and Software Engineering Scientist at the International Centre of Insect Physiology and Ecology (icipe) is responsible for providing strategic leadership in digital systems for research and development. This includes overseeing data management, software development, cloud pipelines, and artificial intelligence. The scientist will serve as the technical coordinator for data throughout all stages of research, developing digital platforms and generating high-quality data products. Key initiatives include managing data stewardship for the Digital Earth Africa program, the Vector Atlas, and other scientific software systems, while leading machine learning solutions (including large language models) for domains such as entomology, ecology, and disease research across Africa.

Key Responsibilities

• Infrastructure Management: Coordinate research on-premises and cloud infrastructure, ensuring the maintenance and evolution of data and software systems.
• Resource Mobilization: Contribute to grant writing and proposal development to secure funding for data-driven research and digital infrastructure.
• Leadership: Act as a corporate leader in data management, establishing a culture that treats data as a cross-corporate asset.
• Policy Development: Align institutional data management policies with regulatory, legal, and ethical mandates.
• Standards & Tools: Develop and maintain data management standards and review emerging tools for timely introduction to the Centre.
• Software Development: Supervise the creation of databases, web systems, and software for the collection, storage, and distribution of research data.
• Risk Management: Maintain data/software audit trails and quality controls to manage corporate data risks.
• Data Governance: Oversee the integrity, security, and availability of institutional data, ensuring compliance with protection and privacy requirements.
• AI & ML Research: Advance modeling and implement novel AI and machine learning initiatives, including large language models.
• Deployment: Deploy internal and external-facing AI applications using cutting-edge data science and software engineering practices.
• Interoperability: Coordinate scientific project components requiring a centralized data clearinghouse to ensure accessibility.
• Optimization: Manage cloud resources for performance and cost-effectiveness.
• Capacity Building: Facilitate training in data management, R, and Python; mentor software developers, data analysts, and graduate students.
• Scientific Contribution: Lead the drafting and publishing of high-impact manuscripts.

Qualifications and Experience

• Education: PhD in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• Research Experience: At least 4 years of postdoctoral experience in managing complex research data and software/cloud systems, including machine learning artifacts.
• Technical Experience: Minimum of 7 years’ experience in designing data collection architectures and software/cloud solutions.
• Contextual Knowledge: Previous experience at an international or regional research organization is an added advantage.

Core Competencies and Skills

• Proficiency in programming with Python, R, or related languages.
• Strong expertise in version control systems, CI/CD, and Agile (Scrum) development.
• Deep understanding of data security, governance, and protection requirements.
• Proven track record of publishing high-impact scientific manuscripts.
• Ability to provide technical guidance and training in information systems and machine learning.

How to Apply

Interested and qualified candidates should apply online through the icipe recruitment portal at recruit.icipe.org. Application details can also be viewed via the official icipe portal.