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by bart_spoon
2257 days ago
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> I've always suspected since that it was someone massaging figures in Amazon to justify their job. Well the first rule should be looking skeptically at someone whose "analysis" involves something their core business provides/sells. Facebook and Google have been pushing data driven narratives about how effective their advertising is, and yet as a data scientist working at a large Fortune 500 company, we never were able to show meaningful impact anywhere close to what was claimed. This was met with pushback, as before my team was created the company relied on external analytics vendors who always came back with results that were magically what everyone was expecting/hoping for. But when my team tried to recreate what they had done, they would withhold information claiming it they were "trade secrets", or what they did provide was riddled with egregious errors. I actually think that is the biggest argument as to why every company should have some kind of data science team. There is certainly important predictive models and analytics to be done, but the most consistent ROI would be to keep the company grounded and not dropping huge sums of money on the trendiest snake-oil analytics/AI solutions being hawked by vendors. |
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This was why I left my last job managing a Data Science team at a large company. It's nearly impossible to complete with a slidedeck from an external vendor that shows exactly what people want to see. Especially when decision-makers and check-signers move on to different jobs in 2 years, so there is nobody to answer why that was done in the first place. Arguing against those vendors brings out the worst in the interested parties and you become the bad guy.