Quantitative Research / Statistics / Sampling Expert

SRD Center is seeking a qualified Quantitative Research / Statistics / Sampling Expert to support a mixed-methods research assignment focusing on migration dynamics, potential migration, information needs, migration intentions, and related socio-economic factors in Iraq.

The assignment will include a large-scale quantitative survey targeting approximately 1,000–1,200 respondents in Baghdad and Basra, alongside complementary qualitative research and stakeholder mapping.

The Quantitative Research / Statistics / Sampling Expert will provide technical leadership for the quantitative component of the study, including sampling methodology, fieldwork preparation, data quality assurance, data management, statistical analysis, and interpretation of findings.

The Expert will work closely with the Team Leader/Senior Research Expert, Field Coordinator, field teams, and data processing staff to ensure that the survey is conducted according to sound social science research standards.

Tasks:

The Expert will be expected to:

• Develop and/or refine the quantitative research methodology and sampling strategy.
• Design a representative sampling approach for the target populations in Baghdad and Basra.
• Advise on sample allocation across governorates, districts, and relevant respondent groups.
• Provide technical input into the survey questionnaire and ensure consistency with the research objectives.
• Support adaptation and pre-testing of the quantitative research instrument.
• Develop data quality assurance and quality control procedures for field implementation.
• Contribute to the preparation and delivery of enumerator training.
• Support the Field Coordinator in monitoring quantitative data collection.
• Review incoming field data for completeness, consistency, accuracy, and potential data quality problems.
• Develop or supervise data cleaning, coding, validation, and management procedures.
• Ensure that datasets are properly anonymised and handled according to applicable data protection requirements.
• Conduct statistical analysis using appropriate quantitative analysis software.
• Produce tables, graphs, cross-tabulations, and other statistical outputs.
• Conduct disaggregated and location-specific analysis where appropriate.
• Interpret quantitative findings and identify major patterns and trends.
• Integrate quantitative findings with qualitative evidence and stakeholder mapping.
• Contribute substantially to drafting the methodology, findings, analysis, conclusions, and recommendations of the research report.
• Support preparation of data visualisations and the executive summary.
• Respond to technical comments and contribute to revision and finalisation of research outputs.

Qualifications:

Candidates should meet the following requirements:

• University degree, at minimum a Bachelor’s degree, in statistics, econometrics, social sciences, research methods, economics, demography, or another relevant discipline; a Master’s degree is preferred.
• At least 5 years of relevant professional experience in quantitative research, data collection, and statistical analysis.
• Demonstrated experience in survey design and implementation.
• Strong experience developing sampling methodologies for large-scale surveys.
• Demonstrated experience in quantitative data management, cleaning, validation, and analysis.
• Proficiency in statistical analysis software such as SPSS, STATA, R, or equivalent.
• Experience working with CAPI-based surveys is highly desirable.
• Experience with research involving migration, displacement, returnees, vulnerable populations, labour markets, or socio-economic issues is an advantage.
• Previous research experience in Iraq or the wider Western Asia/Middle East region is highly desirable.
• Ability to translate complex quantitative findings into clear analytical conclusions and practical recommendations.
• Excellent analytical and report-writing skills.
• Good written and spoken English.
• Arabic language skills are an advantage.
• Ability to work effectively within a multidisciplinary research team and under tight timelines.