The Statistician/Epidemiologist will provide advanced technical leadership in quantitative analysis, study design, and data interpretation across ICRHK’s research and programme portfolios.

The role is central to ensuring scientific rigor, methodological soundness, and credibility of evidence generated by the organization. The successful candidate will support the design and implementation of high-quality research studies and evaluations and translate complex data into actionable insights that inform programming, policy, and global knowledge on sexual and reproductive health and related fields.

This position plays a critical role in strengthening ICRHK’s reputation as a leading research and evidence-generating institution.

Duties & Responsibilities

Statistical Analysis & Data Interpretation

• Lead advanced statistical analysis of quantitative data from research studies, surveys, surveillance systems, and programme evaluations
• Apply appropriate statistical techniques, including multivariate analysis, regression modelling, longitudinal analysis, and impact evaluation methods
• Interpret and synthesize complex datasets to generate meaningful, actionable insights for technical and non-technical audiences
• Ensure consistency, accuracy, and reproducibility of all analyses

Study Design & Methodological Leadership

• Provide technical input into the design of research studies, including experimental and quasi-experimental designs
• Develop sampling strategies, sample size calculations, and statistical analysis plans
• Contribute to the development of research protocols, data collection tools, and study documentation
• Ensure that methodologies align with international standards and ethical guidelines

Programme Evaluation & Learning

• Support the design and implementation of programme evaluations, including baseline, midline, and endline assessments
• Work closely with programme teams to define indicators, measurement frameworks, and evaluation questions
• Contribute to learning agendas by identifying key research questions and analytical approaches
• Support integration of evaluation findings into programme improvement and adaptive management

Research Outputs & Scientific Writing

• Lead and contribute to the preparation of high-quality technical reports, manuscripts, policy briefs, and conference abstracts
• Support the publication of research findings in peer-reviewed journals and dissemination through scientific and policy platforms
• Collaborate with multidisciplinary teams to translate data into compelling narratives and evidence products
• Ensure adherence to publication standards and authorship guidelines

Data Quality Assurance & Management

• Work closely with the MEL Systems & Digital Health Lead to ensure data is clean, well-structured, and analysis-ready
• Develop and implement data quality checks, validation processes, and documentation standards
• Ensure proper data management practices, including version control and reproducibility of analyses
• Contribute to the development of standard operating procedures (SOPs) for data handling and analysis

Proposal Development & Technical Support

• Provide statistical and methodological input into grant proposals, including study design, sampling, and analysis plans
• Contribute to budgeting for research and evaluation components
• Support development of results frameworks and indicators from an analytical perspective
• Participate in donor discussions as a technical expert where required

Capacity Strengthening & Collaboration

• Mentor junior staff and support capacity building in data analysis, interpretation, and research methods
• Provide technical guidance to programme teams on data use and interpretation
• Collaborate closely with the MEL and Research team to ensure alignment between data systems, analysis, and reporting
• Foster a culture of analytical rigor and continuous learning within the organization

Position Attributes / Details

• Minimum of 5–8 years of experience in statistical analysis and research within public health or development settings
• Demonstrated experience working with large, complex datasets from surveys, routine data systems, or clinical/research studies
• Proven track record in contributing to or leading peer-reviewed publications and scientific dissemination
• Experience in impact evaluations, operational research, or implementation science is highly desirable 
• Knowledge of data visualization tools is a plus?