Key Responsibilities:

Lead quantitative research design for evaluations, diagnostics, baselines, endlines, longitudinal studies, and impact assessments.

Develop sampling strategies, power calculations, indicator frameworks, analysis plans, and econometric approaches.

Design and review survey tools, codebooks, data dictionaries, and quality assurance protocols.

Clean, merge, structure, and manage large-scale primary and secondary datasets.

Conduct advanced statistical and econometric analysis, including regression modelling, difference-in-differences, propensity score matching, panel data analysis, heterogeneity analysis, and robustness checks.

Build analytical models for segmentation, scoring, prediction, targeting, or decision-support frameworks, where relevant.

Use secondary datasets such as NSS, PLFS, NFHS, SECC, enterprise datasets, administrative MIS, or other public datasets for research and proposal development.

Prepare analytical tables, visualisations, dashboards, and technical notes.

Translate complex quantitative findings into explicit research narratives for reports, 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 on quantitative methods and data quality.

Ensure reproducibility through clean syntax, documented workflows, version control of datasets, and proper data documentation.

Maintain ethical standards in data handling, anonymisation, confidentiality, and respondent protection.

Requirements

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Essential Qualifications

Master’s degree in Economics, Statistics, Public Policy, Data Science, Development Studies, Population Studies, or related fields.

For RM: 5–7 years of relevant experience in quantitative research, evaluation, analytics, or econometric analysis.

For SRM: 7–10 years of relevant experience, with demonstrated technical leadership across multiple studies.

Strong understanding of quantitative research methods, survey design, sampling, and causal inference.

Strong econometric skills, including regression analysis and quasi-experimental methods.

Proficiency in Stata, R, or Python. Stata/R strongly preferred.

Ability to work with large datasets and produce clean, replicable analysis.

Strong analytical writing skills and ability to explain technical findings to non-technical audiences.

📌 Research Manager / Senior Research Manager (Delhi)
🏢 LEAD at Krea University
📍 Delhi