Wayyy too much info on error
Error is a massive pain in the ass. Most data scientists take the high road …and just ignore it. Eduardo has chosen a different road, the low road, and made it his life's mission to ground, pound, and spit in error's big stupid face. This session will be very good at being a bad personal collection of Eduardo's thoughts, findings, failures, and hail marys that will feel more like a feverish haze of experiences while working at Amazon, federal, and commercial sectors. We'll cover some common and uncommon places where error rears its ugly head. Topics will range from non-technical survey design (Eduardo's passion), ops research framing, to more quant heavy considerations for data types/scales, and even introduce complex methodological techniques and approaches. But, like… in a cool way.
Eduardo is, first and foremost, a big data nerd. Secondly, a recovering data scientist. Currently, a global data director. Also, a public speaker, ex-Amazon, psychologist-by-training, wannabe statistician, AI & university board member, and may or may not have worked for “certain government agencies” in Wash, DC. He prides himself on being able to talk tech good to non-tech folk. The baldness is a choice. The speech impediment is not. The irony is free.