I am a Data Science Manager at Pacific Life Re, where I primarily operate as an individual contributor (Shiny apps linked to actuarial assumptions, 100% local LLM RAG chatbot, ML predictive models, etc) but occasionally help to lead large team projects as scrum master.

I relish the journey of learning, growing and applying my knowledge in data science, machine learning, and AI to build new tools and explore interesting datasets. Perhaps that's why I'm drawn to both my current field and past (investment research & portfolio management) as they are multidisciplinary in nature.

Off work, I enjoy tinkering with open source tools to build and experiment, as well as exploring unusual datasets. Please refer to Project Highlights below for more details.

Building GenAI apps to solve real world problems:

• Multi-Agent Recommender System (GitHub link)
  You want certain coverage but don't wish to spend time crawling through all the different policies out there?
  Let a system of agents help you - they work together to provide personalized recommendations for travel insurance.
  Customizable and scalable.
• AI Voice Assistant (GitHub link)
  Have a fluid life-like conversation when buying insurance.
  Customers’ transcript (unstructured) is converted to structured output which can be used for downstream LLM/ML workflows.
• Podcast Summarizer (GitHub link)
  Too busy to listen to all the interesting podcasts out there?
  Try condensing them into nuggets of wisdom. Utilizes text splitting and multi-step prompting.
• Retrieval Augmented Generation (GitHub link)
  RAG over financial documents. Retrieval methods are evaluated.

ML end-to-end pipeline: What Makes A Cup Of Coffee Memorable?

• Showcased detailed feature engineering pipeline (thresholding, knn imputing, normalizing, etc)
• Trained, resampled, and tuned hyperparameters for LASSO, Random Forest, and XGBoost models, then evaluating models on test data
• Utilized variable importance to understand top predictors across models (one of my created feature ranked highest)

Full list of projects: Python | R

Below is a list of open source technologies (frameworks, libraries, and languages) I regularly use and am familiar with.

🗣️ Programming Languages
Python, R, SQL

🧹 Data Tidying, Visualization, EDA
Python: Polars, Pandas, Plotnine
R: Tidyverse, ggplot2, Shiny

🤖 Machine Learning
Python: Scikit-Learn, XGBoost
R: Tidymodels

🎲 Deep Learning / LLMs
Transformers, PyTorch, Langchain, CrewAI

☁️ Cloud
AWS, Github, Bitbucket