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I've seen a few similar articles now. Does this represent the general view of folks working in data science? "Data Science" is such as meaningless catch all ter
by rafiki6 7y ago
I've seen a few similar articles now. Does this represent the general view of folks working in data science? "Data Science" is such as meaningless catch all term. The reality is in many organizations it's simply advanced business intelligence or advanced business analytics. There are some industries that lend themselves well to this whole practice, and they tend to be industries that have been borne out of the internet age (e.g. social media, internet advertising, etc.)
Some other industries have been doing "data science" for ages. Credit Risk Modelling, insurance and so on.
Every time I read one of these articles, I feel it's just an individual who entered a kind of crummy situation and they're learning what it means to work in a corporate environment. Some are better than others. Some are more motivated than others. Some have better cultures than others. Some are more willing to make technology a key part of their business strategy. Some are more data driven than others.
My recommendation is to always ask the fundamental question before joining: what are you trying to achieve with data science, and is it actually achievable?
- antipaul 7y ago100% agree with the article. The top misconceptions are spot on. I’m at a big place where data science hype among leadership couldn’t be bigger.
- rafiki6 7y agoIf I may ask, what were you told when you interviewed that convinced you to join?
- antipaul 7y agoReasons for joining: 70% just needed a job, 20% location (silicon valley - wanted to be in tech ecosystem), 10% was combo of: I was told it's a small, entrepreneurial team with undefined remit (so opportunities to forge own path - turned out to be true) and it was impressive in many non-technical ways (company mission, campus, resources, etc) And no reasons relating to technical or data science know-how on the part of the team/company ;) I already knew coming in that the industry is technologically backwards (big healthcare co)
- smeeth 7y agoI always thought the non-specificity of the term Data Science was a strange criticism for those in the tech industry to make. How many types of SWE are there? Front-end, back-end, full-stack, devops, security, QA... I agree wholeheartedly with your recommendation. Like any other job, each company has different needs and expectations and if you want something else out of the role you'd best avoid that company.
- rafiki6 7y agoFrankly I have the same criticism of those who use the term software engineer. Engineering is a pretty established profession with a set of standards, ethics and practices. Most of us who work in software are not engineers. We are developers. Similarly, a scientist is one who follows the scientific method to do research. So by that logic a data scientist should be a person who uses the scientific method to do research on data. Does that make any sense? And let's be serious, is that what most data scientists are being hired to do?
- smeeth 7y agoI'd be best described as an ML Researcher/Engineer and I'm not in the private sector so take my opinion with a grain of salt, but my understanding is that many DS roles require application of the scientific method. A lot of DS can be boiled down to some sort of statistical testing or inference (A/B test email marketing for example) or applied ml (classification, regression). I'd argue thats science (if done right). Data Analysis, the plot a few charts and put it in a slide deck kind? Totally agree with you. Definitely not science.
- VHRanger 7y agoA decent amount of data scientists work on AB tests which is science on production data. Actually I'd say that's as common as the failed ML projects
- mr_toad 7y ago> the scientific method to do research on data Exploratory data analysis is often overlooked and underrated.