Salt Lake City Metropolitan Area
I help engineering teams turn raw data into reliable, production-grade insight. For more than 12 years, I’ve designed and delivered hands-on Python, pandas, and XGBoost training for clients ranging from two-person startups to NASA, Adobe, HP, Intel, Cisco, and Samsung. My sessions are built around each company’s own code and data, so students leave with working notebooks and measurable gains—faster pipelines, cleaner models, shorter debug cycles. Beyond the classroom, I advise data-tool vendors such as Ponder on developer outreach and product direction, and my books (Effective Visualization, Effective Pandas, Effective Polars, Machine Learning Pocket Reference, Effective PyCharm) have guided thousands of readers. Online, an audience of 200 k+ follows my daily tips and walkthroughs, making my channels a testing ground for new ideas and a magnet for lively debate. I speak at PyCon, SciPy, PyData, and Stanford Continuing Studies, have co-chaired the Utah Python group, and remain a code-first practitioner: every workshop, talk, or post comes from problems I’m solving in the wild. Need your team writing faster, safer Python? Let’s put your data on the projector and level up together.
Customized Python and Data Science training. Courses bring students up to speed in Beginning Python, Advanced Python, Visualization, Pandas, Polars, Machine Learning (Scikit-Learn, XGBoost, UMAP), Testing, Jupyter Notebook, and Python Packaging, and more. Taught at small companies, universities, and large companies (Adobe, HP, Cisco, Samsung, and more). Predictive modeling to classify job posting industry based on job description. Created a predictive model to determine pricing and time on market for automobiles. Created an NLP model to cluster similar documents and view changes in topics over time. Created an automated custom reporting to provide customer service reps to have insight into customer, their needs, and how they fall relative to other customers in their category. Used to nip churn and find out how the best of breed are using product. Temporal predictive model for churn. Allows interaction with user while they are still engaged with product. Survival analysis of product churn. Modeling complexity using clustering of features, used to determine how to adopt and change input to be more effective. Worked in conjunction with other researchers to pull and munge data. Analysis of product usage: crawling data, ETL, exploratory analysis, visualization, and summaries using iPython Notebook, Pandas, SciKit-Learn (PCA, Random Forests, Decision Trees, KMeans Clustering, Hierarchical Clustering), survival analysis. Web application for video subscription service. Python, JavaScript, AWS, Postgres, Nginx, Django, S3, Stripe. Developed web application for CRE marketplace. Python, JavaScript, Angular, Docker, REST, Postgres, AWS, Django, Nginx, S3, requests, Sendgrid, Zendesk, Digital Ocean. (Sep 2016-Jan 2017) Architecting scalable distributed systems on AWS and Docker. Logic in Clojure and Python. Review of online content for Python courses for online High School. Other projects include. Investigation into porting effort of legacy code to Python.
- Applied ML: Foundations - Applied ML: Value Estimation - Applied ML: Supervised Learning - Applied ML: Ensemble Learning - Applied ML: Algorithms - Applied ML: Feature Engineering - Python for Finance Course - Essentials of Stats with Python Course
Develop and deliver content for Exploratory Data Analysis course with Python for continuing education.
Advising on developer relations, content, and product. Pandas for enterprise!
Create and deliver courses in Python, pytest, pandas, machine learning (clustering, classification, regression, pca), and visualization (Seaborn).