A — Research Conceptualisation & Design
- Problem formulation: framing research questions; constructing testable hypotheses/propositions; literature synthesis and gap identification; developing conceptual/theoretical frameworks
- Understanding of skill ecosystem: Prior work or academic experience of skill ecosystem
- Methodological design: selecting research paradigm (quantitative / qualitative / mixed); choosing design (survey, experiment, case study, ethnography, longitudinal); operationalising constructs into measurable variables
- Sampling design: probability vs. non-probability strategies; sample-size and power estimation; weighting and representativeness; frame construction
- Instrument development: questionnaire and item writing; interview/FGD protocol design; scale development, piloting and validation
- Research governance: ethics and informed consent; securing IRB/ethical clearance and administrative approvals; data-protection and privacy compliance

B — Data Collection & Fieldwork
- Primary collection: survey administration (CAPI/CATI/paper); interviewing (rapport,



probing, active listening); structured observation and field recording
- Field operations: enumerator recruitment, training and supervision; fieldwork logistics and scheduling; real-time monitoring
- Secondary data acquisition: sourcing administrative and government datasets; extraction, compilation and linkage; assessing provenance and fitness-for-use
- Data quality assurance: back-checks and spot validation; consistency and range checks; audit trails

C — Data Management & Analysis
- Data preparation: cleaning, de-duplication and outlier handling; missing-data treatment; coding, structuring and codebook/metadata documentation
- Quantitative analysis: descriptive statistics; inferential testing and regression; advanced methods (multivariate, psychometrics/IRT, equating, causal inference); tool fluency (R, Python, SPSS, Stata)
- Qualitative analysis: thematic and content analysis; grounded-theor

📌 Sr. Analyst (Delhi)
🏢 NSDC India
📍 Delhi