R

Proficiency Level: 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.

Core R Skills

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 and 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 and Applications

Actuarial Applications:

  • Built simple reserving models using chain ladder methods
  • Developed basic GLMs for frequency and severity modeling in academic projects
  • Conducted mortality studies using Kaplan-Meier estimation and survival analysis

Statistical Methods:

  • Fitted GLMs using Poisson and gamma distributions
  • Performed time series decomposition and forecasting (e.g., 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

R 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

I continue to build on my R foundation by:

  • 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.