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Snigdha Das

Snigdha Das

Professor

James Madison University

Technologies

My Portfolio Highlights

My New Course

Introduction to Python

My New Course

Introduction to Python

Data virtuoso, playing the chords of information to create harmonious insights.

My Work

Take a look at my latest work.

course

Introduction to R

course

Introduction to Python

course

Intermediate Python

course

Introduction to R

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Introduction to Python
Introduction to R
Intermediate Python
Data Manipulation with pandas

My Work Experience

Where I've interned and worked during my career.

University of Virginia | Jul 2022 - Present

Principal Investigator

• Experiment Design: Designed, developed, and executed a novel economics experiment to study corruption in the lab. • Led the development of research protocols for Institutional Review Board evaluation and approval. • Managed budget, recruited 175 undergraduate students as subjects, and coordinated 20 experiment sessions in the Veconlab. • Supervised and trained 2 undergraduate research associates to assist in conducting experiments.
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University of Virginia | Aug 2019 - Present

Graduate Researcher

randomized experiment design, diff-diff, and IV techniques for my thesis work in Common Pool Corruption. • Excel: Used excel to calculate Best Response Functions and data visualization for the coordination game in corruption. • R: Used complex Linear Mixed Modelling for analysis experiment data with clustering around subjects. Extracted and interpreted Current Population Survey (it is a monthly survey of about 60,000 U.S. households conducted by the Bureau of Labor Statistics and the Census Bureau, primarily for labor force statistics) data to infer trends in male and female working-age populations under different family structures using R. • SAS: Simulated a Monte Carlo sample and estimated a logistic regression model for predictive analysis. • Qualtrics: Designed the Economics Department’s Graduate Student Survey. • MATLAB: Estimated Bayesian Vector Autoregressions (VARs) for time- series data. This data was meticulously sourced from the U.S. Bureau of Labor Statistics (BLS), ensuring reliability and relevance. • Time Series and Cross-Section Econometrics: Finished the full econometric sequence in my second year and feel very comfortable with econometric and computational modeling (Bayesian VARS, NLP, ML etc).

My Education

Take a look at my formal education

PhD in EconomicsUniversity of Virginia | 2024
MA in EconomicsUniversity of Virginia | 2018
BA(Hons) in EconomicsMiranda House, University of Delhi | 2016

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