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African Population and Health Research Centre , Amentum , Kenyatta University Teaching, Referral and Research Hospital (KUTRRH), Mogo Kenya Limited , Oasis OutsourcingProfession (Entry and Basic-level)
Industry (Entry and Basic-level)
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Non-profit + 1 more
Description
Education
Currently enrolled in or recently completed a Bachelor’s or Master’s degree in Social Sciences, Statistics, Economics, Development Studies, Data Science, Public Health, Nutrition or a related field. Coursework or specialisation in monitoring & evaluation, research methods, or applied data analysis is desirable.
Experience
- At least 1–3 years of practical experience in data collection, enumeration, M&E, research, or community-based program work — paid, volunteer, internship, fieldwork, or research assistant experience all count.
- Hands-on experience using mobile data collection tools such as KoboToolbox, ODK, CommCare, or SurveyCTO in real field settings, including handling sensitive or confidential data.
- Some exposure to data quality checking, cleaning, or verification — spotting inconsistencies, flagging missing data, and following up with sources.
- Experience working with vulnerable, diverse, or community-based populations, with demonstrated commitment to ethical data handling, informed consent, and confidentiality, is a strong plus.
Skills & Competencies
- Comfortable with Excel and/or Google Sheets for organizing and analyzing data.
- Detail-oriented and methodical — catches the small things in a dataset, a tool, or a protocol that others miss.
- Strong written communication: can document what you did, what you found, and what should change, in a way someone else can act on.
- Strong interpersonal and facilitation skills — able to build trust with field teams, school staff, and community members from a wide range of backgrounds.
- Curious, coachable, and proactive: asks why, takes feedback well, and follows through without being chased.
- Working proficiency in English and Kiswahili required; additional Kenyan or regional languages are an added advantage.
Responsibilities
Measurement systems & data quality (~60%)
- Support the Senior Associate, Data Systems, Quality & Analysis to build and refine digital data collection tools (KoboToolbox, ODK, SurveyCTO, CommCare or equivalent) for routine monitoring across schools, kitchens, and field activities.
- Run regular data quality checks on incoming monitoring datasets — looking for completeness, consistency, missing values, outliers, and adherence to indicator definitions — and document issues for follow-up with field teams.
- Help maintain indicator definitions, data dictionaries, and tool change logs so that what we measure stays standardized across regions and over time.
- Conduct basic descriptive analyses of monitoring data in Excel, Google Sheets, STATA, R, or Python to help the team see what is happening in the field and surface anomalies early.
Field data collection & quality (~40%)
- Support the Senior Associate, Field Monitoring & Accountability to plan and prepare data collection rounds with school leads, RPDAs, customer service teams, and other field roles.
- Co-facilitate enumerator and field team trainings on tools, protocols, ethics, informed consent, and confidentiality — and help develop simple training materials, checklists, and job aids.
- Conduct field visits to selected schools and county sites to observe data collection in practice, troubleshoot issues, and bring back ground-truth that improves tools and training.
- Support pilot tests of new tools and indicators, document what works and what doesn’t, and help iterate before full roll-out.
- Cross-cutting
- Help document standard operating procedures, QA protocols, and field guides so the next person inheriting this work has a clear playbook.
- Participate in team learning sessions, sprint reviews, and OKR check-ins, and present your own work and findings on a regular cadence.
- Take on stretch assignments aligned to your learning goals — for example, supporting an evaluation, contributing to a learning brief, or running a focused analysis.
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