A comprehensive view of technical capabilities spanning programming, machine learning, statistical modelling, medical imaging, and data engineering — built through academic rigour and applied research.
| Skill | Context | Proficiency |
|---|---|---|
Python Primary language for ML, data processing, API development |
Chegg · TCG CREST · Personal Projects |
|
R Statistical computing, ggplot2 visualization, survival analysis |
B.Sc. Statistics · Chegg · Research |
|
LightGBM / XGBoost Gradient boosted trees for classification and regression |
Glioblastoma ML · Hackathons |
|
Bayesian MCMC Posterior inference, hierarchical models, uncertainty quantification |
M.Sc. Data Science · Research |
|
PyRadiomics / SimpleITK Radiomic feature extraction, MRI preprocessing pipelines |
TCG CREST Research |
|
Survival Analysis Kaplan-Meier, Cox regression, time-to-event modelling |
PharmaQuant · Chegg · Coursework |
|
SQL / Hadoop ETL pipelines, distributed data processing, HDFS |
NIELIT Data Science Internship |
|
Docker / FastAPI ML model packaging, REST API development, reproducible pipelines |
MLOps · Personal Projects |