Why this matters
Few people are hired straight into a data scientist post. Knowing the realistic routes, what the hiring process looks like and how to grow on the job helps you aim well and avoid discouragement when the first applications do not work out.
Routes in
- Data or business analyst: the most common stepping stone. Do excellent reporting, then volunteer for forecasting, experiments or modelling tasks.
- M&E officer or research assistant: common in NGOs and research projects, including many in Northern Ghana. Survey design, inference and evaluation are central here.
- Internships and national service postings: a chance to work on real data under supervision. Ask for a project with a clear question you can later describe in your portfolio.
- Junior data scientist roles: fewer, often at larger companies or remote, and competitive.
- Data challenges and freelance analysis: build a track record, but be careful with unpaid "test projects" that look like free work.
What the hiring process often includes
- CV screening: keep it to one or two pages, lead with projects and results, and link your portfolio.