Data Analyst Intern (M&E & Impact Analytics)
AI summary
GoKazini is hiring a Data Analyst Intern in Nairobi to support M&E and impact analytics work. The role suits recent graduates with strong quantitative skills and exposure to data tools. Estimated pay is KES 20,000–35,000 per month on-site.
- Internship role suitable for recent graduates
- Focus on M&E and impact analytics
- Estimated salary KES 20,000–35,000/month
- On-site position in Nairobi
- Requires strong quantitative and data analysis skills
AI job guide
Use this guide to check salary signals, requirements, documents, application steps and safety before you apply.
AI salary guide
Source salary availableThe source lists Est. KES 20,000 – 35,000/mo. Confirm the final pay, benefits, contract terms and allowances directly with the employer before accepting an offer.
Can you qualify for this role?
- UnclearRelated work experienceThe text mentions experience, but the exact level should be confirmed at source.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in cleaning, internship, no_experienceThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in Not specifiedThe vacancy is associated with this location.
- UnclearComfort with the Internship contract termsConfirm hours, duration, probation and benefits at the original source.
Documents to prepare
- Likely requiredUpdated CV
- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
- VerifyID or passport only after verifying the employer
Application tips for this job
- Place your strongest Data Analyst Intern (M&E & Impact Analytics) evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to GoKazini and the role in Not specified.
- Add concrete examples related to cleaning, internship, no_experience, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from GoKazini; avoid sending documents to unofficial contacts or copied links.
- Confirm the deadline, interview location and employer contact before sharing personal documents.
Source and safety check
- GoKazini
- Original source link available
- Application method is clear
- Deadline not specified
- No major risk signal was detected in the captured text.
Never pay for interviews, shortlisting, medical checks, uniforms, or job placement. Confirm every application at the original source before sharing personal documents. Report suspicious listing.
Interview preparation
- What experience makes you a strong fit for this Data Analyst Intern (M&E & Impact Analytics) role in cleaning, internship?
- How have you handled responsibilities similar to those in this job post?
- Are you available to work in Not specified under the listed contract or schedule?
- Prepare examples with clear responsibilities, tools used and measurable outcomes.
- Review the source and research GoKazini before the interview.
Ask what the first priorities will be in the role and how success will be measured.
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Original source description
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- KE
- Data Analyst Intern (M&E & Impact Analytics)
- Members only
- Nairobi, Kenya
- Est. KES 20,000 – 35,000/mo
- Est.
- On-site
- Internship
- Entry-level
- Posted
- today
- Share
- What you bring
Education
- Minimum Bachelor's Degree in Statistics, Data Science, Computer Science, Economics, Mathematics, Environmental Studies/Sciences with strong quantitative coursework, or a related field.
- A Bachelor's Degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or Environmental Studies/Sciences is
Preferred Qualifications
for this role.
Experience
- Recent graduate within the last two years, with foundational exposure to data tools.
- Coursework or recent work
- involving M&E, research methods, GIS, public policy analytics, or environmental impact data is a plus.
- Strong analytical thinking and attention to detail.
- Ability to work with spreadsheets and data cleaning workflows.
- Familiarity with data collection and visualization tools (e.g., KoboToolbox, ODK, Excel, Power BI, Tableau, or Google Data Studio).
