Case Study: Home Equity company

At the beginning of 2021, I started working for a home-equity company. They are the biggest platform in the country to list properties that you want to sell. Basically they have all kinds of information on data points on the actual property, including ownership, what years the property was sold, tax information, and photos of the actual property. I am pretty sure you know which company I’m talking about. I cannot disclose the name since I’m still under NDA.

What we used to do there was just basically (why they enrolled me) to help them push for this home flipping unit that they had. And then the home flipping unit was going to generate all this data for properties that were sold in the surrounding areas of that specific property and then calculate automatically the cost of rough investment that will take to flip that unit and then start making money.

So long story short, they invested over 700 million on that business unit, and they suffered about 70% hit on their shares, in late 2021, due to the pandemic. Home prices going down across the country.

So, the point that I’m trying to illustrate here is that they derried a lot of data, there were many data points, we had a data lake, a neural network, and I was in charge of the project that took care of all the data parts from their original app into data points that will make sense to their home flipping unit.

So in that project I was in charge of a team of five people. There were three solutions engineers, one solution architect, and one business analyst; the QA team, they were all part of the parent company so we didn’t have anything to do with them. We only created the test cases for them to test things out and provide the approval for our test cases. We were reporting directly to the technology office of the home flipping unit.