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.
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 80% of the data-- visualized as a predicted confidence interval (upper limit, lower limit, and average prediction), which it then applies test data (the remaining 20% of the data) to see how accurately the model (which is randomly calibrated— "trained" with a randomly selected 80% of the crime-correlated data— when you click) predicts real data.
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
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.
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)Learn about this project