The Alliance of Bioversity International and CIAT on behalf of IITA Recruiting:
 CONSULTANT - DATA ANALYST (NRS) 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. The Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation (https://alliancebioversityciat.org/ )

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.

The Alliance a member of the CGIAR Consortium (www.cgiar.org  ) a global research partnership for a food-secure future.

The International Institute of Tropical Agriculture (IITA)

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

Through the 'ZAMCOM project', IITA is collaborating with ZAMCOM to (i)-Develop a regional catalogue for climate-smart TAAT vetted technologies for the Zambezi basin. (ii) - Generate data and model-driven agronomic (Fertilizer, sowing time, and variety) recommendations. This work will also be part of the CGIAR Sustainable Farming Science Program (SFP), which responds to renewed public and private sector demand for scalable agronomic innovations as an engine for agricultural development through the delivery of agronomic gain in the Global South. SFP will combine big data analytics, AI, and modelling-related technologies, geospatial tools, and farming system research to improve spatially explicit agronomic recommendations in response to demand from scaling partners. SFP is conceptualized around 8 'Areas of Work', one of which (AoW2: Precision Nutrient Management) generates soil nutrient recommendations.

The successful individual will be responsible for supporting interdisciplinary teams to help the ZAMCOM project and SFP to develop and use common approaches for data standardization, analytics and modeling, validation of analytics outputs, and to interface these outputs with external \"consumers--\" (e.g., agricultural advisory developers). Thus, key activities where support from this position is expected include: (i) - Development and or refinement of digital data collection techniques; (ii) - Standardization of legacy agronomy related data sets; (iii) - Supporting efforts to develop common approaches for analytics and modelling; and (iv)- Development of hyperlocalised agronomic (Fertilizer, sowing date and varieties) solutions through use of standardized data and modelling tools (process based and machine learning). The successful candidate will work closely with the community of scientists within the CGIAR, IITA, and other partners to fulfill these activities.

Main duties and responsibilities include:

• Support the development/refining of standards-based digital tools to collect field trial and survey data.
  
• Use and further develop an existing workflow to annotate and upload standardized FAIR data to CGIAR repositories.
  
• Develop/refine existing scripts and tools for advanced statistical analysis that can augment, curate, aggregate, and analyze agronomic data.
  
• Utilize process-based and machine learning models for spatial and temporal crop yield prediction for decision support.
  
• Training of machine learning models using legacy agronomy data sets to generate hyperlocal fertilizer recommendations.
  
• Contribute to developing digital decision support tools to deliver tailored agronomic recommendations to partners and take part in testing and debugging of digital and analogue tools.
  
• Maintain manuals for decision-support tools and documentation on scripts, procedures, specifications, and reporting of relevant data sources (e.g., describing structure, format, and how to access and use them).
  
• Maintain excellent documentation of scripts, procedures, specifications and reporting of relevant data sources (e.g., describing structure, format and how to access and use them.
  
  

  Requirements

  Qualification and Experience
  

  • Bachelor's degree or higher in Data Science, Computer Science, Information Technology with experience in agriculture (preferred), or agriculture degree with strong data science experience.
    
  • At least three (3) years of relevant work experience with key strengths in data management, analytics, and modelling.
    
  • Experience using process-based crop (DSSAT, APSIM) or empirical (Machine learning) modelling tools is necessary.
    
  • Advanced experience in programming (R and/or Python preferred).
    
  • Experience in using collaborative tools and platforms for software development (e.g., Git and GitHub) and methods to maintain code integrity, documentation, and standards is an added advantage.