Data Analyst and Coordinator Intern
AI summary
GoKazini is hiring a Data Analyst and Coordinator Intern based at 63 Westlands Road, Nairobi. The role targets entry-level candidates with a bachelor's degree in data science, statistics, computer science or a related field, and at least one year of data analysis experience. Familiarity with Python, R, SQL, Tableau, Power BI, statistical methods and machine learning is advantageous.
- Internship role based in Westlands, Nairobi
- Entry-level position with estimated pay of KES 25,000–40,000 per month
- Requires bachelor's degree in data science, statistics, computer science or related field
- At least 1 year of data analyst or similar experience expected
- Python, R, SQL, Tableau, Power BI and machine learning knowledge is an added advantage
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 25,000 – 40,000/mo. Confirm the final pay, benefits, contract terms and allowances directly with the employer before accepting an offer.
Can you qualify for this role?
- Required1+ years of relevant experienceThe job post includes a minimum experience signal.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in internship, no_experience, technologyThe 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 and Coordinator Intern 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 internship, no_experience, technology, 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 and Coordinator Intern role in internship, no_experience?
- 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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- HL
- Data Analyst and Coordinator Intern
- Members only
- 63 Westlands Road, Nairobi, Kenya
- Est. KES 25,000 – 40,000/mo
- Est.
- On-site
- Internship
- Entry-level
- Posted
- 2 days ago
- Share
- What you bring
- Bachelor's Degree in data science, statistics, computer science or a related field.
- At least 1 year of
Experience
- as a Data Analyst or in a similar role.
- Proficiency in data analysis tools such as Python, R, or SQL will be an added advantage.
- Advanced knowledge of data visualization tools (e.g., Tableau, Power BI, or equivalent).
- Strong understanding of statistical methods and predictive modeling.
- Familiarity with machine learning frameworks.
- Knowledge of data governance and data privacy regulations.
- GK