About

Hi! I’m Titus, a data scientist since 2014 with a background in pure maths. I work primarily on applying data science tools and methods in the healthcare space where I build predictive models for various healthcare outcomes and costs. It is a challenging field where we need to deal with large (100M+ patients) highly imbalanced datasets (<1% with target conditions), and where model explainability, bias and fairness play a huge impact on the decision making. In my work, I enjoy exploring and prototyping new solutions using either established effective methods or state-of-the-art techniques while helping more junior teammates grow. Finally, I enjoy making an impact not only to the business but to the people we serve.

In this personal blog, I want to share latest things that I find about data science, career, and occassionally my interests. One way to consolidate your learning is by sharing it to others (Feynman Method). I hope you find some useful things here from time to time.