Data Analyst
HybridKampala, Central Region, Uganda
Job Summary
Conduct data quality checks on field-collected farmer and farm data following standard operating procedures and investigate issues outside your remit. Evaluate the effectiveness of newly implemented processes and produce recurring and ad-hoc analysis of field operations performance. Document findings, prepare reports, and transform technical results into material suitable for non-technical audiences. Provide support to the support desk and field staff when required, keeping your supervising Data Analyst informed through regular daily and weekly updates. Draft training materials, protocols, and other necessary documents as needed. This structured graduate programme begins with four weeks of paid induction in Kampala covering data quality control and agricultural insurance context, followed by live project work on country portfolios. Performance during the programme is the route to appointment as a permanent Data Analyst.
Required Qualifications
- Bachelor's degree, completed or completing, in Statistics, Quantitative Economics, Economics, Agricultural Economics, Agribusiness Management, Actuarial Science, GeoInformatics, Information Systems, Computer Science or a related quantitative field
- Working knowledge of Python or R: you can load an unclean dataset, clean it, summarise it, and explain what you found
- Proficiency with spreadsheets beyond the basics, including pivot tables, lookup functions and conditional logic
- Ability to communicate complex information effectively through clear writing and excellent verbal communication skills
- Skilled in collaborating with diverse groups, partners, and colleagues, demonstrating a strong team spirit
- Self-driven, able to work independently with minimal supervision
- Efficiently handle multiple tasks, prioritize work, and meet deadlines effectively
- Careful and attentive to detail
- Legally entitled to work in Uganda
- Available to work from our Kampala office for the first four weeks and on scheduled days thereafter
Desired Qualifications
- Knowledge of SQL
- The second of Python or R
- Proficiency in data visualization tools like Power BI or Tableau
- Stata or SPSS
- QGIS or other geospatial analysis exposure
- Experience with ODK, KoboToolbox, SurveyCTO or similar mobile data collection platforms
- Familiarity with agriculture, agricultural research, or rural fieldwork
- Enumeration or field data collection experience of any kind
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