Head of Data and Research Methods Unit at IITA - International Institute of Tropical Agriculture

Description

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 the One CGIAR, a global agriculture research partnership for a food-secure future

The Data and Research Methods Unit is envisioned as a new organizational structure to be created and coordinated by the successful candidate for this position. Below are some indicative responsibilities for this newly-established unit:

• Acting as the primary convener for a smoothly functioning team that includes data scientists, data managers, geospatial scientists, bioinformaticians, biometricians and other key personnel, with formalized participation of legal and other experts as needed.
• Maintaining, revising as necessary, and operationalizing IITA’s data management strategy.
• Ensuring that IITA data is open and FAIR (Findable, Accessible, Interoperable, and Reusable) through the use of common standards, ethically managed, and available via a common database in compliance with CGIAR’s Open and FAIR Data Assets Policy – with long-term archiving in IITA’s institutional repository.
• Assuring that IITA publications are Open Access.
• Implementing robust data governance and compliance and working with other relevant IITA units (including those dealing with project management and reporting, legal issues etc.) to incentivize best practices in relation to data management.
• Facilitating access to and incentivizing use of ready-to-deploy tools and capabilities by IITA researchers and partners that enable digital collection of FAIR data and render high-value historical data FAIR.
• Enabling unified access to data systems and seamless integration across tools and services facilitate and speed up the research cycle, including cost-optimized compute/store solutions (with collaborative capabilities where needed).
• Institutionalizing and incentivizing open and FAIR data assets by addressing lack of knowledge, attitude, skills and habits (KASH) by developing SoPs, building the data science and data management capacity of IITA scientists and their partners, organizing hackathons etc.

Position Responsibilities:

• Establish, lead, and manage a new Data and Research Methods Unit at IITA, bringing together siloed data and associated management efforts (e.g., bioinformatics, soils, GIS, breeding, agronomy) under a single DRMU umbrella.
• Assume responsibility for developing and managing a budget for the DRMU.
• Building on the draft IITA data management strategy and ongoing developments at the CGIAR level, finalize a strategy and operational plan for the Unit that addresses needs and brings clarity to teams, their roles, responsibilities, reporting, and unit functions. Apart from these, the strategy should:
  • Identify mechanisms for at least partial cost recovery of the unit.
  • Develop a structure, staffing plan, and timetable for filling positions.
  • Identify KPIs for the DRMU and its sub-teams, along with key deliverables for the short (1 year) and medium term (3 years).
• Develop a communication plan to ensure that all IITA staff are aware of the role of the unit, the support it provides, and the responsibilities of both IITA and DRMU staff.
• Identify existing products, tools, and approaches across IITA and CGIAR that enable FAIRER (Findable, Accessible, Interoperable, Reusable, Ethical, and Replicable) data, and develop a strategy to minimize duplication of effort and institutionalize their use.
• Establish necessary protocols, procedures, and training plans to assure that IITA data management adheres to CGIAR policy and more broadly to FAIRER principles.
• Enable the generation of value from a harmonised data infrastructure for the institute, e.g., direct calculation of key performance indicators on numbers of partners reached, partners involved, use of research products, etc. by gender, technology, crop, and more - across all IITA projects and research domains.
• Identify needs and facilitate a training program to enable IITA scientists to use relevant data science approaches.
• Develop processes and incentives to ensure that staff comply with FAIRER data management policies and procedures, formalizing links with IITA’s legal and project management teams to track FAIRER data through a project’s life cycle.
• Advise management on how processes and incentives to assure FAIRER data should be implemented (e.g., with explicit indicators included in scientist evaluations).
• To make sure that IITA makes the most of the diverse data it produces, keep abreast of projects involving IITA staff, foster the exchange of research data between these where appropriate, and encourage data-driven multidisciplinary projects resulting in high-impact publications.
• Stay abreast of developments in data management, data analysis, and scientific computing methods, to ensure that IITA is following best practices.
• Stay up to date on requirements from IITA programs and staff on data management and research methods, assisting scientists to adopt best practices and new data management and analytics technologies where appropriate.
• Oversee IITA’s scientific computing infrastructure and make strategic decisions pertaining to it.
• Liaise with IITA’s ICT Unit on hardware and software requirements to ensure effective, efficient, and secure data management and scientific computing capacity.
• Contribute to scientific research and communication (up to 20% FTE).
• Perform any other job-related duties as assigned by the supervisor.

Requirements

Educational Qualifications and Experience

The candidate should have a PhD in agriculture with significant data science expertise, or other advanced degree with demonstrated experience in data science applied to agricultural issues.

Core Competencies

• At least five years of experience working in a similar role.
• Strong understanding of and experience working with agricultural data management, in at least one but ideally across domains (e.g., agronomy, plant breeding+) and analytics including large (e.g., spatial) data, ideally including machine learning approaches.
• Strong statistical background with demonstrated application to agricultural data.
• Experience with FAIR data principles and with developing or using common data standards for interoperability (e.g., ontologies, controlled vocabularies).
• Familiarity with user-centered design principles and development of dashboards.
• Familiarity with API development and the Open API Specification.
• Strong expertise in R, Python; experience with json, xml, html, java suite, and/or other relevant programming languages, and methodologies like Agile Scrum a plus.
• Familiarity with project and code management tools (e.g., GitHub, Atlassian tools, SourceForge etc).
• Persuasive professional, with demonstrated ability to collaborate with and bring together individuals and teams from diverse professional and cultural backgrounds for consultatively developed products.
• Experience developing product profiles, pipelines, and managing towards impact-focused solutions.
• Self-motivated critical thinker and team player, with strong problem-solving skills.
• Strong written and oral communication skills.
• Ability to reliably meet deadlines and deliver high-caliber outputs.
• Advanced fluency in English.