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Key Responsibilities:
Lead quantitative research design forevaluations, diagnostics, baselines, endlines, longitudinal studies, and impactassessments.
Develop sampling strategies, power calculations, indicator frameworks, analysisplans, and econometric approaches.
Design and review survey tools, codebooks, data dictionaries, and qualityassurance protocols.
Clean, merge, structure, and manage large-scale primary and secondary datasets.
Conduct advanced statistical and econometric analysis, including regressionmodelling, difference-in-differences, propensity score matching, panel dataanalysis, heterogeneity analysis, and robustness checks.
Build analytical models for segmentation, scoring, prediction, targeting, ordecision-support frameworks, where relevant.
Use secondary datasets such as NSS, PLFS, NFHS, SECC, enterprise datasets,administrative MIS, or other public datasets for research and proposaldevelopment.
Prepare analytical tables, visualisations, dashboards, and technical notes.
Translate complex quantitative findings into clear research narratives forreports, decks, policy briefs, and donor-facing documents.
Support proposal development by designing credible methodologies, sample plans,analytical frameworks, and costing assumptions.
Guide junior researchers, Research Associates, interns, and field/data teams onquantitative methods and data quality.
Ensure reproducibility through clean syntax, documented workflows, versioncontrol of datasets, and proper data documentation.
Maintain ethical standards in data handling, anonymisation, confidentiality,and respondent protection.
Requirements
EssentialQualifications
For RM: 5–7 years of relevant experience inquantitative research, evaluation, analytics, or econometric analysis.
For SRM: 7–10 years of relevant experience, withdemonstrated technical leadership across multiple studies.
Strong understanding of quantitative researchmethods, survey design, sampling, and causal inference.
Strong econometric skills, including regressionanalysis and quasi-experimental methods.
Proficiency in Stata, R, or Python. Stata/Rstrongly preferred.
Ability to work with large datasets and produceclean, replicable analysis.
Strong analytical writing skills and ability toexplain technical findings to non-technical audiences.
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