Getting my models dunked on by people who can't open MS Outlook more than 3 tries out of 5, however, have a
remarkable depth and insight into their chosen domain of expertise. It's rather humbling.
Collaborating with nontechnical people is oddly my favorite part of doing MLE work right now. It wasn't the case when I did basic web/db stuff. They see me as a magician. I see them as voodoo priests and priestesses. When we get something trained up and forecasting that we both like, it's super fulfilling. I think for both sides.
Most of my modeling is healthcare related. I tease insights out of a monstrous data lake of claims, Rx, doctor notes, vital signs, diagnostic imagery, etc. What is also monstrous is how accessible this information is. HIPAA my left foot.
Since you seemed to be asking about the temporal realities, it's about 3 hours of meetings a week, probably another 3 doing task grooming/preparatory stuff, fixing some ETL problem, or doing a one-off query for the business, the rest is swimming around in the data trying to find a slight edge to forecast something that surprised us for a $million or two using our historical snapshots. It's like playing wheres waldo with math. And the waldo scene ends up being about 50TB or so in size. :D
Collaborating with nontechnical people is oddly my favorite part of doing MLE work right now. It wasn't the case when I did basic web/db stuff. They see me as a magician. I see them as voodoo priests and priestesses. When we get something trained up and forecasting that we both like, it's super fulfilling. I think for both sides.
Most of my modeling is healthcare related. I tease insights out of a monstrous data lake of claims, Rx, doctor notes, vital signs, diagnostic imagery, etc. What is also monstrous is how accessible this information is. HIPAA my left foot.
Since you seemed to be asking about the temporal realities, it's about 3 hours of meetings a week, probably another 3 doing task grooming/preparatory stuff, fixing some ETL problem, or doing a one-off query for the business, the rest is swimming around in the data trying to find a slight edge to forecast something that surprised us for a $million or two using our historical snapshots. It's like playing wheres waldo with math. And the waldo scene ends up being about 50TB or so in size. :D