"Beyond your failures and fears lie opportunities." — Reetika

As I approach the final stage of my PhD, I am actively seeking industry opportunities in pharmaceutical/healthcare statistics and research software development. If you have any questions about my educational background, professional experiences, or areas of passion, I would be happy to discuss them.

My ideal career involves working alongside dynamic, compassionate, and resilient individuals committed to positively impacting the world. Throughout my academic journey and graduate industry internships, I’ve been fortunate to learn from outstanding professionals and scholars. Along the way, I’ve become proficient in multiple programming languages, including R, Python, SAS, and JSL, and I’m eager to apply my skills and enthusiasm to the industry.

Education

2021 - 2025

University of North Carolina at Greensboro (UNCG)

PhD in Computational Mathematics (Statistics)

Research Topic: Statistical Learning Methods for High-Dimensional Data with Complex Correlation Settings.

Coursework: Bioinformatics • Complex Data Analysis • Statistical Computing • Statistical Consulting • Statistical Methods • Statistical Linear Models • High-dimensional Data Analysis • Theory of Linear Regression • Spatial Statistics • Categorical Data Analysis • Data Science (using Python)

2015 - 2017

University of Delhi

M.Sc. in Statistics

Coursework: Probability Theory • Design of Experiments • Sampling Theory • Stochastic Process • Statistical Inference • Linear Algebra • Multivariate Analysis • Generalized Linear Model • Bayesian Inference • Biostatistics • Econometrics and Time Series Analysis • Demography, Statistical Quality Control & Reliability

Research & Teaching Experience

January 2021 - Present

Department of Mathematics and Statistics, UNCG

Doctoral Researcher/Graduate Teaching Associate

Led a comparative study of regularization approaches for variable selection under different correlation structures, and pioneered the development of a two-stage procedure, rPGBS, to enhance stable variable selection in complex, high-correlation environments.
Led an in-depth study to enhance the classical Apriori algorithm for safety signal detection in post-marketing data, uncovering potential associations between drugs/vaccines and rare adverse events (AEs).
Mentored undergraduate students in the Research Experience for Undergraduates (REU) program.
Instructed and tutored over 500 students in undergraduate Math and Statistics courses.

March 2017

Department of Statistics, University of Delhi

Graduate Research

Conducted independent research to study the effect of socio-economic factors on the life expectancy of humans using Gapminder datasets.

Professional Experience

May 2024 - Aug 2024

JMP, SAS

Clinical Graduate Intern

Conducted double programming and unit testing in JMP Scripting Language (JSL) to validate safety analysis reports generated in JMP Clinical using CDISC format clinical data.
Jun 2023 - Aug 2023

Novartis Pharmaceuticals

Pharmacometrics Intern

Developed an interactive R Shiny app for exploring and modeling Dosimetry data in RadioLigand Therapy (RLT), a nuclear precision medicine for cancer treatment.

Aug 2011 - Dec 2020

Ministry of Women & Child Development, Government of India

Assistant Section Officer

Structured policy-making for schemes related to nutrition and early childhood care and education of children, and welfare of young girls in India.

Computing Skills

R • SAS • JMP • JSL (JMP Scripting Language) • Python 3.0 (matplotlib, plotly, scikit-learn, pandas, NumPy, SciPy) • SQL • MS Excel • LATEX • Monolix • Jupyter Notebook • GitHub • Minitab • C • SPSS

Selected Certifications

SAS 9.4 Base Programmer (August 2024)
Crash Course in Causality: Inferring Causal Effects from Observational Data by Coursera (April 2024)
AI for Medicine Specialization by Coursera (July 2023)
Drug Development Overview and General Oncology Module 1: Biology of Cancer by Novartis (August 2023)
SAS Visual Statistics on SAS Viya: Interactive Model Building by SAS (May 2023)
Deep Neural Networks with PyTorch by Coursera (August 2022)