Sr. Analyst (Research)

National Skill Development Corporation (NSDC); Delhi; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

National Skill Development Corporation (NSDC) invites applications for a Research Conceptualisation & Design role. You will craft research questions, design methodological frameworks, and plan sampling, instrument development, governance, data management, and reporting.

You will lead data collection (survey and fieldwork), ensure data quality, and perform both quantitative and qualitative analyses. You will translate insights into actionable recommendations for policymakers and stakeholders.

Qualifications

• Masters or above in Economics, Statistics or Data Science.
• Engineers with Data Science/ML/Analytics background.
• Others from Social Science background considered on merit.

Responsibilities

• Frame research questions and hypotheses; literature review and gap analysis.
• Design methodological approach and sampling strategy; select survey/qualitative methods.
• Develop data collection instruments and protocols; ensure ethical and privacy compliance.
• Coordinate fieldwork; supervise enumerators; manage real-time field operations.
• Manage data cleaning, coding, and metadata documentation.
• Analyze data using descriptive and inferential statistics and qualitative methods; triangulate results.
• Interpret results and prepare policy-relevant findings for dissemination.

Skills

Quantitative analysis

Qualitative analysis

Data management

Ethics & consent

Fieldwork supervision

Education

Masters or above in Economics

Masters or above in Statistics

Masters or above in Data Science

Engineers with Data Science/ML/Analytics

Tools

R

Python

SPSS

Stata

PowerBI

Excel

PowerPoint

NVivo

Job description

SUMMARY

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-theory coding; QDA software (NVivo, etc.)
• Interpretation & synthesis: pattern and trend identification; triangulation across sources; data visualisation for insight

D Communication, Report writing

• Technical & academic writing: report structuring; publication and manuscript writing; citation and referencing discipline
• Dissemination: presentation and public speaking; data storytelling; conference/workshop facilitation
• Stakeholder engagement & policy translation: policy-brief writing; audience-tailored messaging; advisory and consultative engagement with policymakers, practitioners and the public

E- Transversal / Foundational skills

• Research ethics and integrity; project and time management; digital and data literacy; critical thinking and problem-solving; collaboration and teamwork; multilingual/field-language competence; adaptability under field conditions.

Requirements

Academic Background

• Masters or above in Economics, Statistics, Data Science
• Engineers with Data Science, Machine Learning, Data Analytics
• Any Other candidates from Social Science background can be considered on a case-to-case basis depending on the merit

Experience

• 3-8 years of working experience in the relevant field depending on the requirement of the level.
• Proficient in Microdata analysis using any software package like R, Python, Stata
• Prior experience of working in skill ecosystem
• Deployed ML techniques in analysis
• Proficient in PowerBI, Excel & Powerpoint
• Ability to write analytical reports