At my internship, our big data clients have increasingly come to us with the task of assessing data sets of unknown validity. In these circumstances, many times data providers will perform extensive, time-consuming and expensive analysis on a data set only to find that it severe inconsistencies in the data and ultimately misleading predictive value. To solve this, we have developed the Data Qualification Engine which runs quick analysis and validation of a dataset, identifies any inconsistencies, and runs a simple regression backtest to outline predictive value.
I worked with a team of three as the front-end developer and wireframer. I created the initial task analysis, wireframes, and reporting design and worked with our new designer on the hi-fidelity mockups. I then was responsible for the front-end development as I worked alongside another engineer who focused on our Flask Back-end and report generation.
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