About the role 

Busara Center for Behavioral Economics is recruiting an Associate (Data Systems and MEL Specialist) to support complex, multi-partner programme evaluations and data quality engagements. This is a technically hybrid role designed for someone with formal training in data science, statistics, or information systems who has built their career in monitoring, evaluation, and learning environments — and who understands how data systems and programme realities interact in practice.

The Associate will work across the project lifecycle: from receiving and assessing partner datasets, to supporting data quality diagnostics, contributing to analytical outputs, and communicating findings to both technical and non-technical audiences. This is not a purely analytical role. The post holder is expected to manage their own workstreams, engage with partners directly, and take ownership of deliverables end to end.

Role purpose 

The Associate will ensure that programme data is securely received, technically assessed, cleaned, and made analytically usable, while also contributing to the MEL processes that translate data into learning and programme decisions. The role sits at the intersection of data systems management, data quality assurance, and evaluation practice, and requires someone equally comfortable diagnosing a structural dataset problem and drafting a clear findings brief for a programme team.

Key Responsibilities

Data Systems Management and Governance

• Receive, log, and securely store partner datasets in line with project data management and governance protocols.
• Define and manage data access permissions, ensuring only authorised users can access sensitive or identifiable data.
• Maintain clear handling protocols for raw, cleaned, and anonymised datasets across teams and workstreams.
• Maintain version control and detailed audit trails for all data processing steps.
• Ensure compliance with data protection requirements and ethical data use standards, including relevant East African regulatory frameworks.

Data Quality Assessment and Diagnostics

• Review dataset structure, variable naming, coding, and formatting against project standards and reporting requirements.
• Conduct data quality checks on core variables including, demographics, participation dates, intervention types, and contact details.
• Assess the presence and quality of unique identifiers; detect duplicate or inconsistent records.
• Conduct internal consistency checks across variables, classifications, and timelines.
• Compare partner dataset counts with reported figures and flag and document discrepancies.
• Provide clear technical write-ups of dataset limitations that affect analysis, sampling, or verification decisions.

Data Preparation and Analysis

• Clean and prepare datasets for analysis, sampling, and verification activities.
• Support quantitative analysis of programme and research data, including working with large administrative datasets.
• Contribute to the design and implementation of sampling processes for surveys and follow-up verification.
• Support data visualisation and the development of summary dashboards and analytical outputs for reporting.
• Work with analysts and senior staff to ensure analytical approaches are appropriate, rigorous, and well-documented.

Project and Workstream Management

• Contribute to inception reports, analytical briefs, and final evaluation reports to a high standard of clarity and rigour.
• Manage assigned workstreams end to end, including planning activities, tracking progress, and ensuring timely delivery of outputs.
• Coordinate with internal teams, data, research, and operations,  to ensure alignment across project activities.
• Communicate proactively with project leads on risks, blockers, and emerging issues affecting timelines or quality.
• Contribute to client and partner engagement, including preparation for meetings, workshops, and review sessions.

Knowledge skills and Experience

• 5 years of relevant experience, with a combination of data management or data systems work and practical MEL engagement in development programme contexts.
• Experience working with large administrative or partner datasets in multi-partner programme environments.
• Experience supporting or leading evaluations, data quality assessments, or programme monitoring systems.
• Demonstrated ability to manage projects or workstreams independently, including managing timelines and partner relationships.
• Experience producing written analytical outputs — reports, briefs, or technical summaries — for varied audiences

• Strong command of Excel and at least one statistical or data management tool such as Stata, R, Python, or SQL.
• Ability to detect structural issues in datasets and diagnose data quality problems systematically.
• Familiarity with digital data collection platforms such as KoboToolbox, CommCare, or DHIS2.
• Experience with data visualisation tools such as Power BI, Tableau, or equivalent is an advantage.
• Understanding of data protection and privacy requirements, including in East African regulatory contexts.