Sr. Analyst (Research)

Posted Yesterday
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Delhi, Connaught Place, New Delhi, Delhi, IND
In-Office
Senior level
Social Impact
The Role
Conducts end-to-end research, including problem formulation, study and sampling design, instrument development, fieldwork, data management, quantitative and qualitative analysis, and research governance. Uses R, Python, SPSS, or Stata for microdata analysis and applies machine learning techniques. Develops reports, presentations, policy briefs, and academic publications while engaging stakeholders and ensuring data quality, ethics, and privacy compliance.
Summary Generated by Built In

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

1Academic 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


1Experience:

1.      3-8 years of working experience in the relevant field depending on the requirement of the level.

2.      Proficient in Microdata analysis using any software package like R, Python, Stata

3.      Prior experience of working in skill ecosystem

4.      Deployed ML techniques in analysis

5.      Proficient in PowerBI, Excel & Powerpoint

6.      Ability to write analytical reports


Skills Required

  • Master’s degree or higher in Economics, Statistics, or Data Science
  • Engineering background with specialization or experience in Data Science, Machine Learning, or Data Analytics
  • Social Science background may be considered on a case-by-case basis based on merit
  • 3–8 years of relevant work experience, depending on role level
  • Proficiency in microdata analysis using R, Python, Stata, or another statistical software package
  • Prior experience working in the skill ecosystem
  • Experience deploying machine learning techniques in analysis
  • Proficiency in Power BI, Excel, and PowerPoint
  • Ability to write analytical reports
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The Company
268 Employees
Year Founded: 2008

What We Do

National Skill Development Corporation (NSDC) is an Indian not-for-profit public-private partnership that empowers youth through comprehensive skill development. It supports enterprises, startups, and training organizations with funding, concessional loans, and innovative financial products; coordinates private-sector vocational training initiatives; and serves as a strategic implementation and knowledge partner for the Skill India Mission, helping build a workforce-ready national skills ecosystem.

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