Resume
Interested in working with me?
I’m a Machine Learning Engineer with deep experience across the full modeling lifecycle — from exploratory data analysis and visualization through training, tuning, and deploying production systems. My work spans classification, regression, forecasting, anomaly detection, and neural network inference, with a focus on models that are accurate, resilient, and built to scale.
Work Experience
Staff Machine Learning Engineer / Senior Data Scientist
Square · San Francisco, CA (remote) · Apr 2021–Present
- Built and deployed ML models for high-value initiatives: marketing lead conversion ranking (LightGBM), web traffic classification (PyTorch+Keras), and hardware anomaly detection (Isolation Forests)
- Created mature data & ML ecosystems with robust CI/CD pipelines to support modeling work for broader teams
- Supported a large product team with a wide array of data science and modeling requests while managing contracted roles
Data Scientist
Red Dot Storage · Louisville, CO · Apr 2019–Apr 2021
- Built and deployed financial models to optimize core revenue management through dynamic churn prediction
- Provided leadership with narrative-driven insights via statistical modeling, analytics, and machine learning
Data Scientist / Data Analyst / Lead Developer
Talus Analytics · Boulder, CO · Jan 2018–Apr 2019
- Integrated data analysis, visualization, and design across analytics platforms with emphasis on public health and global security
- Led full-stack development and technical direction of several analytics dashboards
Data Scientist / Software Engineer
Nidhogg Consulting · Boulder, CO · Mar 2016–Jan 2021
- Co-founded as Chief Data Scientist and lead Software Engineer
- Responsibilities included project management, full-stack web development, data science, and new contract acquisition
Applied Math Research Assistant
University of Colorado Boulder · Boulder, CO · Sep 2015–May 2017
- Applied ML models to experimental lab data for data quality prediction (presented at SIAM 2016)
- Built a massively parallel simulation framework for soliton gas dynamics in 1D systems (presented at SIAM 2017)
Summer Internships
| Year | Company | Role |
|---|---|---|
| 2016 | Khan Academy | Data Scientist — probabilistic network infection modeling, SAT score analytics |
| 2015 | Shutterstock | Data Scientist — Apache Spark ETL and big-data solutions on Hadoop |
| 2014 | SpotXChange | Data Scientist — Tableau automation, time-series analysis, probabilistic modeling |
| 2013 | MITRE | Data Visualization — network packet visualization for security CTF |
Skills
Programming: Python, SQL, Javascript / HTML / CSS, Bash / Shell Scripting
Modeling: Machine Learning, Classification, Regression, Forecasting, Anomaly Detection
LLMs & AI: NLP, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Agentic AI
Cloud & Data: AWS, GCP, Databricks, Prefect, Snowflake
Libraries & Frameworks: Polars, Scikit-Learn, Keras, PyTorch, TensorFlow, Pandas, NumPy, SciPy, NLTK, Flask, Matplotlib, Holoviews, D3, Jupyter, Git
Software Engineering: CI/CD, Docker, Unix, Agile Development, Unit Testing
Education
Applied Math B.S., Computer Science Minor University of Colorado Boulder · May 2018