October Edition: Getting Hired in Data Science. To get hired as a data scientist, don't follow the herd. There are plenty of reasons for this (media hype being one of them) but there's no doubt that the job of a data scientist is a highly valued one.
Between hosting the Towards Data Science podcast, and coaching data science mentees at SharpestMinds, I’ve realized that trying to become a data scientist is like drinking from two firehoses. The first firehose is technical. You have to browse blog posts, online courses, Kaggle competitions and bootcamps, and learn about everything from AUC scores and hyperparameter tuning to clustering algorithms and deep neural networks. This one’s a pain to deal with, but it gets a lot of attention, and there are great resources our there to help most people wrap their heads around it, provided they put in the time.
But the second is just as important. This is the career advice firehose — the set of information that helps you to decide what jobs you should target to break into data science, and how you can stand out among the sea of other applicants.
Most people start with the technical firehose, and later move on to the career firehose by looking for jobs that match their technical skills, rather than the other way around. I think that’s a mistake.
Before you know what technical skills you need to learn, you need to know what you want to do. Otherwise, you risk picking up a bunch of generic, unrelated, cookie-cutter data science knowledge that doesn’t add up to a coherent role — or worse, that sets you up for a role you later realize you never even wanted.
So for this newsletter, we decided to put the horse before the cart, and highlight some of the best career tips that TDS authors want you to know about. Whether you’re an aspiring data scientist, or you’re in the middle of your data science career, I’d recommend taking this opportunity to reflect on the career path ahead of you. Enjoy the read!
Jeremie Harris, Podcast Host at Towards Data Science.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
They say, the first impression is the last, and thus resumes are the first impression of any professionals including data scientists while searching for a job.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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If you have other resources, tips, or advice, please leave a comment below and I’ll update this post for others looking to advance their data career.