Well hello.

I'm Patrick, a Business-minded NodeJS developer with experience in Enterprise Application API Integration, Web Application Development, and Business Consulting with corporate and small business executives.

    My technology skillset includes: (view additional business skills)
  • NodeJS Web Development
    • Serverside: NodeJS, ExpressJS (REST API), Enterprise App API integration (CRM, ERP)
    • Clientside: ReactJS, Webpack, Babel, Sass/scss, various data chart API, customized & responsive web design
  • SQL / Relational Database design, querying and application integration
  • Statistical analysis in R and Python, including predictive & descriptive statistics, with R, python, & javascript data visualization packages
  • Linux, Nginx, Git
  • Systems Analysis & Design

Here's an introduction to one of my favorite projects.
It's a predictive model, in an R script, sitting on my server. When you click this button, it samples a set of data (crime in 36 zip codes in Austin, TX) and generates a trained model with ~83% of the data (30/36 data points)-- visualized as a predicted confidence interval (upper limit, lower limit, and average prediction), which it then applies test data (the remaining 17% of the data (6 data points)) to see how accurately the model (which is randomly calibrated— "trained" with a randomly selected 83% of the crime-correlated data— when you click) predicts real data.

Please be patient as it might take a few moments to load. And if you refresh, you can click again for a new prediction.

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Data:
Upper Fit Lower Actual

Here are a some recent projects:

Timetracker App (ReactJS/NodeJS)

An open source web app for tracking timesheets for an hourly workforce.
Includes real time clock in/clock out, geographic mapping of workers, timerange-based lookups, and CRUD admin system


View description & demo

Marketo LiveChat API Project (NodeJS)

While at Pulse Secure, the Director of Marketing requested that I complete a data integration project, which I successfully completed according to both his requirements and the IT Director's requirements. (Technically though, I worked in Operations, as a direct report to VP of Operations.)
The solution: I wrote a script in NodeJS to migrate data from a webchat application (LiveChat) to a marketing application (Marketo), once hourly, (based on a conditional decision model) and log any errors encountered. Then, once per day, a second script would email the admin about any new errors.

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Predicting rates of crime based on economic indicators (R — statistical computing)

As part of my graduate statistics course "Advanced Statistical Methods", using R, I data-engineered a dataset from public datasets, then tested various economic factors for their usefulness in contributing to a predictive model. After finding the right model, I demonstrate a training model and test real data against it. Similar methodology, on a larger scale, could be replicated to attempt to predict business outcomes. (In fact, one project I would like to work on is a web dashboard for statistically derived business metrics)

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Personal technology interests:

  • Electronics & Microcomptuers — One of my life goals is to surround my future house with a lush garden and greenhouse. Raspberry Pi, ESP8266, and similar microcomptuers are fun to play with, and I would like to use them to create customized irrigation systems.
  • Visual analysis with Machine Learning — One upcoming personal project I would like to work on is a machine learning program for automated visual analysis, for security projects and even wildlife cameras. Most of the work has been done by others in this field, and the components can be readily assembled into a system involving a microcomptuer, videocamera, and software. One interesting application: An online network of wildlife web-cameras, which are ranked by amount of wildlife activity, and would include data and charts for wildlife activity trends.