How to Apply: Send your application via email to recruitment@africanguaranteefund.com with the subject line "AGF - Application for Assistant Data Analyst Position". Include your resume and cover letter summarizing your relevant work experience, and the name and contact information of 3 referees familiar with your professional qualifications and work experience.
Show Your Dashboard Impact Before You Walk In
This role lives at the intersection of data, business development, and credit risk. The hiring team wants to see that you can turn raw numbers into decisions that grow SME lending, not just pretty charts.
1. Build a portfolio of dashboards: Bring screenshots or live links of dashboards you've built, especially ones that track business growth or loan performance. Explain the data sources, the metrics you chose, and how leadership used them.
2. Master the tools they use: Be ready to demonstrate advanced Excel (pivot tables, lookups, charts) and SQL. If you know Power BI or Tableau, prepare a short walkthrough of a dashboard you created.
3. Speak the language of credit: Brush up on credit risk metrics like default rates, portfolio at risk, and SME financing gaps. Be ready to discuss how data can reduce risk and improve financial inclusion.
4. Show your CRM chops: If you've used Salesforce, HubSpot, or Dynamics, highlight how you kept data clean and used it to support sales or BD. Mention any reporting you generated from the CRM.
5. Prepare for a case study: You may be given a dataset and asked to analyze it on the spot. Practice cleaning data, creating a pivot table, and drawing insights quickly.
6. Connect data to business outcomes: Instead of just listing technical skills, talk about how your analysis led to a 15% increase in leads or cut reporting time by 20%. Quantify your impact.
7. Understand the sector: Research AGF and the development finance space. Know how credit guarantees work and the challenges SMEs face in East Africa. Show you're genuinely interested in financial inclusion.
8. Polish your communication: You'll need to explain data to non-technical stakeholders. Practice simplifying complex findings into clear, actionable recommendations. Bring an example of a time you did this successfully.