Feb 6
Alright alright alright. Hello, World! Work updates: I've been working on 3 (new) things these couple of months, and all of them are approaching the finish line! (First out of many, so like alpha versions): 1. Optimizing client onboarding process - This went really well, already tested the pipeline. Hot. 2. Inventory Throttling - This feature is my baby and it's really close to deployment. Money. 3. Revenue Projections - Picked up this project from another data scientist couple of weeks ago, and already nearly ready to deploy! Quick and Dirty. The last project is an excellent example of the difference between a good and a bad data scientist. The previous data scientist who was working on revenue projections worked on it for months. Countless Data Science meeting and countless documentations later, there didn't seem to be much clarity on the team. He is a really nice person with a math PhD background, and after talking to him about his ideas in person I realized that they made sense. What was missing though is his ability to get to the point, give tangible examples, and generally - communicate. I'm sure he knew more math and ML than me, but in a way, it didn't matter. What took him months took me 2 weeks and that's the moral of the story - difference between a good and a bad data scientist is literally exponential. And just to be clear, it doesn't take a PhD to be a good data scientist. Bonus: something awesome is coming. API related *wink wink* Something awesome: SEC - watch out!