There's a lot of grey area between engineering and data science for us. To somewhat simplify, we have 17 product engineers, 5 data engineers, and 19 data scientists.
We operate the company in "lanes" like Seller, Buyes, Homes, Accuracy. The "purest" technical challenges are on Accuracy where we're modeling home prices, days on market, pricing strategy, and various measures of risk. A lot of feature engineering, data viz, etc.
On the product engineering side, we start and end with the customer problems, not the technology. Projects range from building a mobile app for inspectors to catch all issues and normalize the data, to building custom security hardware with Raspberry Pi's that relies on mobile SIM cards because we don't own the homes long enough to justify setting up/turning off internet.
You mention 17 product engineers, 5 data engineers and 19 data scientists on board now...what was your launch team like? I assume you've had massive growth / hiring but curious what it looked like at the beginning (in boot strap mode/mvp mode)
We operate the company in "lanes" like Seller, Buyes, Homes, Accuracy. The "purest" technical challenges are on Accuracy where we're modeling home prices, days on market, pricing strategy, and various measures of risk. A lot of feature engineering, data viz, etc.
On the product engineering side, we start and end with the customer problems, not the technology. Projects range from building a mobile app for inspectors to catch all issues and normalize the data, to building custom security hardware with Raspberry Pi's that relies on mobile SIM cards because we don't own the homes long enough to justify setting up/turning off internet.
I can get more specific if helpful!