IE Research Data Manager 1 at Jhpiego - John Hopkins University

Job ID: 2026-7619

Overview

• Jhpiego is seeking to hire a Research Data Manager 1, who will work on the design, management, and execution of all quantitative, monitoring and evaluation (MEL), and methodological components of the Impact Evaluation.
• The role serves as the technical backbone of the evaluation, responsible for ensuring that quantitative findings are valid, reproducible, and methodologically defensible.
• Working closely with the Jhpiego team, this role will translate evaluation questions into robust analytical approaches, manage quantitative datasets, analyze data, generate scorecards, dashboards, and statistical outputs that demonstrate before–after change, contribution, and systems-level impact of C19RM investments.

Responsibilities
Quantitative Evaluation Design & Methods:

• Lead development of the quantitative evaluation approach, including before–and–after and quasi-experimental comparisons where feasible.
• Support refinement of the evaluation framework, theory of change, and indicator matrix.
• Define sampling strategies, inclusion criteria, and analytical assumptions for quantitative components.
• Ensure alignment of indicators with C19RM modules, national frameworks, and donor expectations.

 Monitoring, Evaluation & Indicator Management:

• Serve as the MEL lead for the Impact Evaluation.
• Develop and manage the indicator reference matrix, including definitions, data sources, baselines, and comparison points.
• Ensure consistency and traceability of indicators across datasets, analysis outputs, and reporting.
• Establish and document data quality assurance (DQA) processes, including validation, triangulation, and audit trails.

Data Management & Quality Assurance:

• Oversee quantitative data collection workflows and ensure adherence to protocols.
• Lead data cleaning, validation, and management across multiple sources (routine data, program datasets, surveys).
• Ensure reproducibility of analyses through well-documented datasets and code.
• Identify and address data gaps, biases, and limitations in collaboration with the Team Lead.

Statistical Analysis & Evidence Generation:

• Conduct or oversee statistical analyses, including descriptive analysis, trend analysis, and comparative assessments.
• Generate quantitative outputs such as:
  • Domain-specific scorecards
  • Tables and figures
  • Dashboards and visual summaries
• Interpret findings in collaboration with the Team Lead and qualitative research lead.
• Clearly articulate strengths, limitations, and confidence levels of findings.

Collaboration & Technical Support:

• Provide technical guidance to Research Supervisors and field teams on quantitative tools and data requirements.
• Work closely with the Qualitative Research Manager to ensure integration and triangulation of findings.
• Support the Team Lead in responding to technical queries during validation and review processes.
• Contribute quantitative inputs to technical briefs and presentations as required.

Contribution to Manuscript Development:

• Lead development of quantitative methods sections, statistical analyses, tables, and figures for manuscripts.
• Ensure transparency, reproducibility, and accurate interpretation of quantitative findings.
• Contribute to the results and methods sections and respond to technical reviewer comments related to data and analysis.

Other Duties:

• Perform any other duties assigned by the supervisor in line with the Impact Evaluation deliverable.

Required Qualifications

• Master’s degree or higher in Biostatistics, Epidemiology, Statistics, Health Economics, Evaluation Science, or a closely related quantitative field.
• 7–10 years’ experience in quantitative research, MEL, or impact evaluation within health or development programs.
• Demonstrated experience designing and implementing impact or quasi-experimental evaluations.
• Strong experience working with large routine health datasets and programmatic data.
• Proven ability to deliver high-quality analytical outputs under tight timelines.
• Experience with donor-funded programs and national health systems is strongly preferred.

Required Technical Skills & Software Proficiency:
Quantitative Analysis & MEL Tools:

• Statistical software: STATA (preferred), R, SPSS, or equivalent
• Data management & analysis: Advanced Microsoft Excel (pivot tables, Power Query, complex formulas)
• Dashboards & visualization: Power BI, Tableau, or equivalent (hands-on experience preferred)

Health Information Systems:

• Interpretive and analytical experience with:
  • DHIS2
  • Routine surveillance and health management information systems

Documentation & Collaboration:

• Microsoft Word (technical documentation and annexes)
• Microsoft PowerPoint (analytical presentations)
• Familiarity with collaborative platforms (SharePoint, Teams, Google Workspace)

Knowledge, Skills & Competencies:

• Strong grounding in evaluation methodology and statistical reasoning.
• High attention to data quality, documentation, and reproducibility.
• Ability to explain complex quantitative findings to non-technical audiences.
• Strong problem-solving and analytical thinking skills.
• Ability to work independently while coordinating closely with senior technical leadership.
• Excellent time management and ability to deliver under pressure.

Key Accountability Statement:

• The Research Manager I is accountable for the technical accuracy, integrity, and reproducibility of all quantitative findings generated for the Impact Evaluation.
• All quantitative evidence must withstand technical scrutiny and support defensible conclusions regarding program impact and contribution.