About Pahlé India Foundation

Pahlé India Foundation (PIF) is a public policy think-and-action tank working at the intersection of research, policy implementation, and partnerships to advance India’s inclusive development agenda. PIF collaborates with government, industry, philanthropy, and knowledge partners to design evidence-based solutions aligned with the vision of a Viksit Bharat. For more information, click the link

Role Overview

PIF is seeking a Data Analyst to support rigorous data-driven research and policy analysis. The role will involve building and managing datasets, conducting statistical and econometric analysis, and translating complex data into actionable insights for policy research and governance initiatives.

The candidate will work closely with research teams and government stakeholders to analyse data, support evidence-based decision-making, and contribute to analytical outputs that inform policy reforms and development programmes.

Key Responsibilities

a)Data Collection & Dataset Development

Collect, clean, and structure large-scale datasets to enable rigorous analysis.
Build and maintain high-quality panel datasets with multiple identifiers to support longitudinal analysis.
Manage data pipelines and ensure data integrity across research projects.

b)Data Analysis & Econometric Modelling

Conduct exploratory data analysis to identify patterns, trends, and insights.
Apply econometric and statistical techniques such as fixed effects models, difference-in-differences (DiD), linear probability models (LPM), instrumental variables, and propensity score matching.
Support the development of predictive models and statistical analysis for research studies.

c)Data Visualisation & Insight Generation

Translate complex datasets into clear insights using visualisations, dashboards, and summary statistics.
Develop analytical outputs that support policy reports, research papers, and presentations.
Communicate findings effectively to research teams and stakeholders.

d) Advanced Analytics & Qualitative Analysis

Apply machine learning techniques including regression, clustering, and supervised or unsupervised learning methods.
Use natural language processing (NLP) and sentiment analysis tools to analyse textual data.
Support qualitative data analysis using tools such as NVivo or Atlas.ti where required.

e) Collaboration & Policy Research Support

Work closely with research teams to integrate data analysis into policy research and impact assessments.
Support government-focused projects by generating data-driven insights for policy design and evaluation.
Contribute to analytical frameworks and methodologies for research initiatives.

Qualifications & Experience

Master’s degree in Economics, Econometrics, Data Science, Statistics, or related quantitative disciplines.
Minimum 2 years of relevant experience in data analysis, econometric research, or applied analytics.
Strong academic training in econometrics, statistics, and quantitative research methods.

Skills & Competencies

Strong programming skills in Stata, R, or Python.
Experience applying econometric methods and causal inference techniques.
Familiarity with machine learning techniques such as regression models, clustering, random forest, KNN, and gradient boosting methods.
Experience working with large datasets and statistical analysis tools.
Familiarity with qualitative analysis tools such as NVivo, Atlas.ti, or NLP libraries in Python.
Strong analytical thinking and problem-solving skills with attention to detail.

What We Offer

Opportunity to work on high-impact public policy research projects.
Exposure to real-world governance and economic policy challenges.
A collaborative and mission-driven work environment.
Competitive compensation commensurate with experience.

Application Procedure

Applicants should send their CV along with a cover letter to: priyanka.sharma@pahleindia.org

Note: Only shortlisted candidates will be contacted for further evaluation. Pahle India Foundation is an equal opportunity employer and encourages applications from individuals of all backgrounds.

Pahlé India Foundation (PIF)

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