PROGRAM DESCRIPTION:
 SAFIC is an African-led Centre of excellence at the SBS seeking to empower, enable and scale agri-food innovations, and enhance the competitiveness of food systems across the continent. SAFIC is driven by a clear mission to enhance the competitiveness of the agriculture and agrifood sector in addition to facilitating and supporting innovations within strategic areas of the sector.
JOB PURPOSE:
The Senior Data Analyst will integrate data science solutions to the planning, decision-making, and actor influencing of the Centre. The position holder will design, develop, and validate the effectiveness of data science products and create packages that help communicate data-driven insight and value for engagement with partners for inclusive agricultural transformation in key agrifood value chains. The position holder will lead a team of data analysts, research associates and other data scientists to deliver on the Centre’s data intelligence strategies and product development for the benefit of its stakeholders.
MAIN DUTIES AND RESPONSIBILITIES:

Collate, Collect, Study, explore, and evaluate new and existing data sources (from grey literature to primary data) to determine their usefulness and accuracy for inclusion in decision-making and actionable output.
Design and build predictive data science products, such as visualizations, models, or artificial intelligence/machine learning algorithms for subsequent utilization in commercial solutions.
Analyze qualitative and quantitative data using the latest statistical techniques, interpret data, analyze results, and provide ongoing reports; Engage in complex analyses, simulations, and modeling to develop data products and insights with high predictive accuracy and commercial value.
Design, build, maintain, and continuously improve the self-serve capacities of the Centre’s business intelligence systems, and educate data users across the organization to find answers through important metrics.
Build, mentor, and lead a fast-growing team of data professionals, contributing to the team's technical growth and its future strategy.
Lead teams of data analysts and research assistants and oversee programmatic themes related to data systems.
Work closely with various teams to design and implement new data collection and visualization tools and features.
Liaise with ICT and relevant internal stakeholders to access infrastructure, software, and services needed to develop and deploy data science products.
Work with Senior Research staff to review research, data collection, validation, analysis, and/or reporting to support the development of technical standards, innovative tools, and methodologies to be used within the Centre or by external stakeholders.
Identify and answer strategic business questions with rigorous evidence as well as provide data-driven recommendations to internal and external stakeholders.
Provide leadership in organizing capacity development programs and tools, such as training workshops and seminars, training manuals, materials, online tools, and information kits.

JOB REQUIREMENTS
The post holder will be required to have and to demonstrate evidence of the following qualifications, attributes, and skills:

PhD degree in Data Science, Statistics, Applied Mathematics, Biometrics, Statistical genetics, or a related field from an accredited academic institution with seven years of relevant professional experience; or
MSc. degree in the above or related fields with ten years of relevant professional experience in a high-output environment.
A minimum of seven years of progressively responsible experience in data science, data analytics, applied mathematics, economic analysis, or related areas is required.
Experience in research, data collection, and analysis of agricultural productivity data will be highly advantageous.

DESIRABLE SKILLS:

Data analysis: A strong analytical background and Proficiency in tools like R, STATA, and SPS for data analysis. Knowledge of SAS or Python and visualization tools (e.g. PowerBI, Looker, Tableau) is an added advantage.
Design thinking skills: Proficiency in design thinking principles, with an ability to understand user needs, ideate creative solutions, and prototype user-centered data products and solutions.
Statistical and machine learning skills: Strong statistical and machine learning expertise, particularly as it pertains to agricultural data analysis and predictive modeling.
This should include experience in Regression analysis, Time series analysis, Dynamic modeling, and Bayesian Statistics. Proficiency in current approaches in Machine learning and Artificial Intelligence must be demonstrated.
Data visualization: Proficiency in data visualization tools and techniques, with the ability to create compelling visualizations to communicate agribusiness insights to stakeholders.
Collaboration & Teamwork: Ability to work collaboratively with team members across functional roles and strong communication and leadership skills.
Data Collection: Demonstrated skills in the development and deployment of data collection tools. Proficiency in the use of GIS and other remote sensing data is a bonus.
Text Analysis and Natural Language Processing (NLP): Experience with text analysis and natural language processing techniques, such as analyzing unstructured social data.