R

Intermediate

As a final-year BCom Actuarial Science student, I have developed a working proficiency in R through coursework, academic projects, and personal exploration. I use R for statistical analysis, data visualization, and basic actuarial modeling.

Statistical Analysis

Use of base R for data manipulation and common statistical functions

Familiarity with the tidyverse packages: dplyr, tidyr, ggplot2, stringr, lubridate

Basic understanding of regression, time series, and summary statistics

Actuarial & Analytical Packages

Exposure to ChainLadder and actuar for reserving and actuarial calculations

Used forecast for basic time series forecasting tasks

Familiar with survival package for mortality and lapse studies

Modeling & Applications

Actuarial Applications

Built simple reserving models using chain ladder methods

Developed basic GLMs for frequency and severity modeling

Conducted mortality studies using Kaplan-Meier estimation

Statistical Methods

Fitted GLMs using Poisson and gamma distributions

Performed time series decomposition and forecasting (ARIMA)

Applied PCA and basic clustering for exploratory analysis

Data Visualization

Used ggplot2 to create charts and visual summaries

Developed multi-panel plots and explored custom themes

Familiar with using plotly for adding interactivity

Created reporting templates using R Markdown

Project Work

Reserving Workbook

→Built a small reserving tool using ChainLadder and ggplot2
→Automated calculation steps and added explanatory output
→Presented findings in a reproducible report using R Markdown

Pricing Model Prototype

→Implemented GLM-based pricing models on insurance datasets
→Evaluated model fit and residuals using cross-validation
→Documented assumptions and structure using R Markdown

Programming Practices

Write modular R scripts with clear naming conventions

Comment and document code using roxygen-style or inline comments

Maintain reproducible workflows using .Rproj files and Git

Use renv for managing package dependencies

Ongoing Development

Practicing more advanced modeling and visualization techniques

Exploring Shiny and flexdashboard for interactive reporting

Studying open-source R code to learn best practices

Engaging with the R community through blogs, tutorials, and packages

R has become a valuable part of my toolkit for analyzing data, building actuarial models, and communicating results in a structured, reproducible way.