About Me

A fresh look brought to you by Generative AI


My career includes over 15 years of data science, financial strategy, and business analytics for EY, PG&E, KPMG, Centene, and Bloomreach. I use the R and Python programming languages on a daily basis but am much more advanced with my R work. My teams apply data science techniques to empower decision makers with descriptive, predictive, and prescriptive insights. I sit somewhere between the business stakeholder and cloud engineering to develop and deploy automation pipelines, predictive models, interactive web apps, and simulations.

Scatter Podcast

In 2019, I launched Scatter Podcast to share career tips and insights from data science leaders for students, business managers, and professionals looking to pivot into data science. It was a fun and incredibly rewarding side project but after 30 episodes, I started to feel fatigued with the amount of time it took to plan, record, edit, market, etc. The podcast is on hold but not dead!

Data Science & MLOps Toolkit

  • R: tidyverse, tidymodels, Quarto, webR, XGBoost, Prophet, sparkr / sparklyr, torch, Keras (+ TensorFlow), Shiny, Plotly, Leaflet, package development, dbplyr (communicate with databases by writing in dplyr syntax to create complex [or basic!] ETL and analytics pipelines that convert your dplyr code to SQL in the backend 🚀), and more

  • DevOps + MLOps: GitLab (+ CI/CD), GitHub (+ Actions/Workflows), Databricks (+ MLFlow), Docker, Posit Connect, Kubernetes, Rancher, Ubuntu, Bash

  • Data: Snowflake, Teradata, Apache Arrow, Apache Parquet, DuckDB, AWS S3, AWS Redshift, NetApp StorageGRID, Google BigQuery

  • Other: Python (I’m objectively terrible but w/ ChatGPT I’ve been known to impress myself and my team 🏆), Jupyter Notebooks, Agile Scrum (+ the tools that surround it, e.g., Jira, ServiceNow, Miro, etc.), Netlify

Media + Presentations