Graduate Intern – MEL (Business Engagement Market Systems) at Mercy Corps in Nairobi, Kenya

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    Graduate Intern – MEL (Business Engagement Market Systems)

    Mercy CorpsNairobi, Kenya

    Posted

    1 week ago

    Apply by

    26 Aug

    Full Time
    On Site
    Internship
    Charity, NGO & Non-Profit
    Data, Analytics & AI

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    Job Description

    The Graduate Intern – MEL is a position within the Country MEL team. Under supervision, the Intern will support the management, quality assurance, analysis and use of programme data across the Mercy Corps Kenya portfolio. The Graduate Intern will receive exposure to the MEL cycle, including results measurement, digital data collection, data cleaning and validation, dashboard development, basic statistical analysis, documentation, research support, learning and adaptive management. In this role, the Graduate Intern will gain practical exposure to analyzing market systems, understanding the behavior of market actors, assessing the sustainability of programme results, and evaluating how development initiatives contribute to long-term, inclusive change.

    Key Responsibilities

    • Support the testing, review and documentation of digital data-collection tools and workflows, including CommCare forms and applications.
    • Assist with preparation and maintenance of data dictionaries, indicator mappings, user guidance, system documentation and change logs.
    • Support routine checks on data synchronization, completeness and system functionality, and document issues for resolution by the responsible technical staff.
    • Assist with organizing programme databases, evidence files and MEL records using agreed naming, version-control and access protocols.
    • Provide basic user support and contribute to simple learning materials for programme teams and partners, under supervision.
    • Support data cleaning, coding, validation, deduplication and preparation of programme, participant and partner datasets.
    • Conduct routine data-quality checks for missing values, inconsistencies, duplicates, unusual patterns and incomplete supporting documentation.
    • Assist programme and MEL teams to track and resolve identified data-quality issues while maintaining a clear audit trail.
    • Apply approved confidentiality, access-control, data-protection, anonymization and secure file-handling procedures.
    • Support preparation of validated datasets for reporting, dashboards, research and evaluation activities.
    • Use Excel and other approved tools to produce basic descriptive statistics, summaries, tables, charts and routine analytical outputs.
    • Support the preparation, testing and updating of Power BI dashboards and standardized programme performance reports.
    • Assist with disaggregation and trend analysis by geography, sex, age and other relevant inclusion or programme variables.
    • Support analysis of participant reach, outcomes, service access, partner performance and programme implementation trends.
    • Assist with survey preparation, digital-tool testing, field monitoring, assessments, evaluations and other evidence-generation activities.
    • Support basic quantitative and qualitative data organization and analysis, including coding of structured qualitative information where appropriate.
    • Support analysis of MSD information, including market-actor reach and performance, changes in access and use of services, behaviour and relationship changes, inclusion, sustainability and emerging signs of wider system change.
    • Work collaboratively with Country MEL colleagues, programme teams, partners and relevant regional or global technical teams.
    • Participate actively in supervision, coaching, mentoring, structured learning activities and periodic performance discussions.
    • Maintain accurate records of assigned work, learning progress and completed deliverables.
    • Demonstrate professional conduct, curiosity, integrity, attention to detail and openness to feedback.
    • Perform other closely related learning assignments agreed with the supervisor and consistent with the purpose of the graduate trainee role.

    Required Qualifications

    • A bachelor's degree in data science, Statistics, Applied Statistics, Economics and Statistics, Information Systems, Computer Science, Information Technology, Business Information Technology, Mathematics and Computer Science, Operations Research, Actuarial Science, Monitoring and Evaluation, or another closely related quantitative discipline.
    • Candidates from a technical or computing discipline should demonstrate basic exposure to MEL, research or programme-performance concepts through coursework, academic research, volunteering or self-directed learning.
    • Candidates from Monitoring and Evaluation or a related development discipline should demonstrate foundational quantitative, data-management and digital-systems capability.
    • Graduated within twelve 12 months for bachelor's degree holders; or Awaiting graduation, completed course work
    • Basic understanding of MEL concepts, such as theories of change, results frameworks, indicators, data collection, data quality, analysis, reporting, learning and adaptive management.
    • Foundational knowledge of quantitative and qualitative research methods gained through university coursework, a final-year project, capstone assignment or equivalent academic work.
    • Basic competence in Microsoft Excel, including data organization, formulas, sorting, filtering, tables, charts and preferably pivot tables or lookup functions.
    • Demonstrated interest in learning Power BI, CommCare, databases, SQL, Microsoft Azure and statistical or programming tools such as Stata, SPSS, R or Python.
    • Ability to think analytically, identify inconsistencies, follow procedures and communicate findings clearly in writing and verbally.
    • Strong attention to detail, integrity and willingness to handle confidential information responsibly.
    • Ability to work respectfully and collaboratively in a diverse team and to seek guidance when needed.
    • Proficiency in written and spoken English; working knowledge of Kiswahili is required.
    • Willingness and ability to travel to programme locations.

    Job Details

    Job Function

    Data, Analytics & AI

    Education Level

    Bachelor’s Degree

    Area of Study

    Science

    Field of Study

    Data Science

    Languages

    English, Kiswahili

    Additional Information

    How to Apply: Send your application to the provided email or visit the application link on the original posting.

    Show Your Data Skills in Action

    This internship is your chance to dive into real-world monitoring and evaluation. Hiring managers will look for practical evidence of your data handling abilities, so be ready to demonstrate your Excel and analytical skills.

    1. Tailor your CV: Highlight any coursework, projects, or volunteer work involving data collection, analysis, or MEL. Use specific examples like building a dashboard or cleaning a dataset.

    2. Master Excel basics: Ensure you can confidently use formulas, pivot tables, and charts. Be prepared to discuss how you've used these in academic or personal projects.

    3. Show interest in learning tools: Mention your eagerness to learn Power BI, CommCare, SQL, or Python. Even basic familiarity can set you apart.

    4. Understand MEL concepts: Brush up on theories of change, indicators, and data quality. Be ready to explain how you'd apply them in a development context.

    5. Prepare for a practical test: Many MEL roles include a data exercise. Practice cleaning a sample dataset and creating a summary report.

    6. Communicate clearly: Your ability to explain data findings in simple terms is crucial. Practice presenting a data insight to a non-technical audience.

    7. Emphasize attention to detail: Highlight times you caught errors or improved data accuracy. This is a key trait for MEL roles.

    8. Be ready to travel: Show flexibility and willingness to work in the field. Mention any experience working in diverse teams or communities.

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    Tags

    MEL
    data analysis
    Power BI
    Excel
    CommCare