Data and Software Engineering Scientist at icipe - International Centre of Insect Physiology and Ecology

Overall Purpose of the Job

The scientist is responsible for providing strategic leadership of in digital systems in research and development, such as data management, software, cloud pipelines and artificial intelligence. The scientist will manage data and serve as the technical coordinator for data throughout all stages of research and development. The scientist will develop/implement digital platforms and collate data for analysis and generate high-quality data products/outputs. The scientist will lead and coordinate all cloud and data engineering inputs, manage complex data stewardship in the Digital Earth Africa program, the Vector Atlas, and other related scientific software systems. The scientists will lead the development of machine learning (including large language models) solutions in various domains (such as entomology, ecology, diseases, etc.), for Africa and beyond

Specific Duties

• Manage and coordinate all research on-premises and cloud infrastructure with respective data and software systems to ensure the overall maintenance and evolution.
• Contribute to resource mobilization; grant writing, and proposal development to secure sustainable funding for data-driven research and software/cloud infrastructure development.
• Be the corporate leader in data management and work with staff to establish a vision and culture that embraces data management and accountability as a cross-corporate asset.
• Develop and align the institutional data management policy with relevant regulatory, legal, and ethical mandates.
• Develop and maintain data management standards for the Centre and regularly review emerging data management tools and skill and ensure timely introduction to the Centre.
• Supervise the development of relevant databases, web systems, and other software for the collection, storage, and distribution of research data.
• Develop and maintain data/software audit trails, controls on data quality and interoperability to manage corporate data related risks.
• Manage programmes that advance the roles of data management and oversee the integrity, security, usage and availability of institutional data management policy while ensuring compliance with data governance, protection, privacy, and security requirements across systems and architectures.
• Advance modelling and conduct research to implement optimized/novel artificial intelligence and machine learning (including large language models) initiatives and solutions.
• Deploy internal and external-facing artificial intelligence applications using cutting-edge data science and software engineering practices.
• Coordinate diverse scientific project components that require a centralized data clearing house to ensure interoperability and data accessibility.
• Optimize cloud resources and products for performance and cost-effectiveness.
• Develop and facilitate in-house data management training courses and the use of R and
• Python statistical software for scientists and students.
• Enhance capacity building by supervising and mentoring software developers, data analysts, and (post)graduate students.
• Contribute and lead the drafting and publishing of high-impact manuscripts.

Requirements/Qualifications

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

Core Competencies

• Experience programming in Python, R, or related languages is required.
• Experience providing training and technical guidance to enhance the development of institutional capacity to use information systems, data science, and machine learning.
• Good understanding of version control systems, CI/CD, Agile (Scrum) development, data security, and governance.
• Publication of high-impact manuscripts