Is Data Science Dead? Long Live Business Science
255 days ago
World's Most Popular 5 Hardest Programming Language
Looking For Data Science Jobs: The Perfect Data Scientist Doesn't Exist
- Start working on it, and
- If stuck, ask for guidance.
- Pros: They have business expertise. They know how to make a good looking chart that lands with leadership.
- Cons: They don't have experience in programming. They're comfortable with using Excel and SQL only, and may not have the ability or desire to learn programming. The fact that they are into their career and haven't learned programming is a red flag.
- Would I hire them: Yes, if they have the intelligence and motivation to learn to program.
- If you are this person: Learn to program! There are tons of courses out there on how to learn R or Python. Take some of these and then do something with that knowledge. Anyone can watch a presentation, but using your new abilities to do something like compete in a Kaggle competition is what will set you apart.
- Pros: They know how to work in SQL, and how to make pretty charts. They get things done!
- Cons: They don't know how to take the data they present and infer meaning from it (that's someone else's job). They don't know how to program.
- Would I hire them: No, unless I see evidence that they can learn how to both program and draw insight from data. BI and analytics have totally different roles. BI is to set up the data backend, analytics is to use that data to make decisions. A BI person needs to prove that doing analytics won't overwhelm them.
- If you are this person: If you want to be a data scientist, move to the role of business analyst first. This will give you a small taste of what data scientists do. If you like being a business analyst but wish you could go deeper, then consider data science.
- Pros: They've done this job before! In theory they should do great on my team.
- Cons: They may be out of my price range. They may be bored by doing mundane data cleaning or exploratory analysis. They also may not have experience in presenting and working with a client.
- Would I hire them: Yes, but I have to balance my team so it isn't filled only with people who make models and do deep data science. I need some people to do the more mundane stuff too.
- If you are this person: congratulations you will have no trouble finding a job somewhere. You probably know that already.
- Pros: They're eager to learn new skills and do well. They often have some mathematics and statistics, and have done a bit of programming. They are willing to do more "grunt labor" tasks.
- Cons: They don't have any business experience. They haven't had their spirits broken by the harsh realities of the 9â??5 job.
- Would I hire them: Absolutely! These people don't take as long to ramp up as you would think, and want to succeed. Before hiring them they need to show that they can get things done, like having had an internship, a side project, or a particular compelling class project.
- If you are this person: Having a high GPA isn't important, showing that you can get things done is.
- Pros: Knows math and statistics and how to program. Is very intelligent.
- Cons: Academia doesn't teach you how to get things done. If they wanted to go to academia then they enjoy working on the most intellectually stimulating problems for the thrill of it. That's very different than working on the problems that are most important to a business.
- Would I hire them: No. If I were to hire them they would probably be unhappy working under me. This job has lots of time spent doing uninteresting tasks like data aggregation. During the first few months, they're probably going to spend a lot of lunch breaks alone in their car screaming about how meaningless it all is, and I don't want to be there for that.
- If you are this person: Before you leave academia go get an internship or industrial experience. That will show you know what working a 9â??5 job is actually like and you are still into it.
- Pros: potentially has more business acumen than someone with a STEM degree.
- Cons: Their coursework may have taught them a few data science techniques, but not the deep understanding of how they work and why. they wont know how to program.
- Would I hire them: No. Having a business analytics focused MBA is a signal that they didn't want a math, statistics, or data science degree. It's a lot easier to teach someone who knows how a logistic regression works to use it on business data than to teach someone who understands business how a logistic regression works.
- If you are this person: You are qualified for a business analyst job, and there are lots of those! You'd be happier with one of those than with a data science job. You can start as a business analyst and work your way up if you so choose.