Two field supervisors are needed to lead enumerator teams, manage field logistics and safeguard data quality.
Field Supervisor (2 Positions) at Insight Axis Africa in Nairobi, Kenya
Posted
1 week ago
Apply by
30 Aug
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Build My CVTwo field supervisors are needed to lead enumerator teams, manage field logistics and safeguard data quality.
Job Function
Data, Analytics & AI
Minimum Experience
2 years
Education Level
Bachelor’s Degree
Area of Study
Social Sciences
Field of Study
Social Sciences
Languages
English
How to Apply: Visit the application link provided on this page to submit your application.
Field supervision is about protecting data quality when the ground gets messy. Hiring managers will want to see that you can lead teams, catch errors early, and keep logistics tight.
1. Prove your CAPI fluency: On your CV, list the specific platforms you've used (ODK, SurveyCTO, KoBo) and describe how you used them to monitor data quality. Mention any dashboards or reports you built to track enumerator performance.
2. Quantify your supervision scope: Instead of just saying you supervised enumerators, give numbers: how many people, how many households, how many days in the field. This gives a concrete sense of your scale.
3. Prepare for scenario questions: Expect questions like 'An enumerator is fabricating data, what do you do?' or 'A village is inaccessible, how do you adjust your plan?' Think through your answers ahead of time, focusing on your decision-making process.
4. Show your logistics muscle: Fieldwork runs on transport, accommodation, and supplies. Give an example of a time you managed logistics under a tight budget or deadline, and what you learned.
5. Highlight your training skills: You'll need to train enumerators quickly and effectively. Describe a time you trained a team on a new protocol or tool, and how you ensured they understood it.
6. Emphasize your reporting discipline: Daily reporting is key. Show that you can produce clear, concise updates that help the research coordinator make decisions. Mention any reporting templates or routines you've used.
7. Know your sampling basics: Be ready to discuss sampling methods (random, stratified, cluster) and how you've implemented them in the field. Review the basics before the interview.
8. Show you care about team welfare: Fieldwork is tough, and a good supervisor keeps morale high. Talk about how you've supported team members in difficult conditions, and why that matters for data quality.
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