Role Overview
Position Overview
As a Data Analyst at Pula, you will play a crucial role in supporting the Analytics & Insights Analysts by ensuring data management and analysis, problem identification, resolution, and the implementation of department strategies. We are looking for highly motivated and data-driven individuals with strong documentation skills, capable of careful, methodical work under supervision.
This is a structured graduate programme rather than an unstructured placement. You will join a cohort that is recruited, trained and supported together, with a dedicated Data Analyst as your supervisor throughout.
The Programme
The first four weeks are a paid induction at our Kampala office, covering data quality control methodology, Pula’s field data pipelines, the analytical toolset, and the agricultural insurance context in which the work sits.
From the fifth week, you move into live project work on one of Pula’s country portfolios, working alongside experienced analysts. The work is consequential: the data you check determines whether farmers are correctly registered and correctly paid.
Prior professional experience is not required. This is a graduate programme, and we expect to be the first or second employer of most successful applicants. Candidates are assessed on demonstrated capability at the screening stage rather than on length of service.
Responsibilities
Key Responsibilities
- Conduct data quality checks on field-collected farmer and farm data following standard operating procedures (SOPs).
- Investigate and resolve data issues, escalating matters that fall outside your remit.
- Identify gaps in current data quality check SOPs and suggest improvements.
- Evaluate the effectiveness of newly implemented processes.
- Produce recurring and ad-hoc analysis of field operations performance.
- Document findings, prepare reports, and make recommendations based on analysis.
- Transform technical results into material suitable for non-technical audiences.
- Provide support to the support desk and field staff when required, ensuring effective communication.
- Utilize data analytics and project knowledge to identify risks and issues within projects.
- Keep your supervising Data Analyst informed by providing regular daily and weekly updates.
- Draft training materials, protocols, and other necessary documents as needed.
- Utilize designated tools and software proficiently as per project requirements.
- Emphasize direct and open communication to address problems and provide feedback constructively.
- Demonstrate honesty and transparency in all aspects of work. Early disclosure of a problem is always preferred to late discovery.
Requirements
Who you are
- 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. This is tested directly at screening stage.
- 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. Data quality work rewards those who notice small discrepancies.
- Legally entitled to work in Uganda.
- Available to work from our Kampala office for the first four weeks and on scheduled days thereafter.
Also an advantage
- 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.