The Most Important Job in the World Is Not Computer Science but Engineering

In a post titled “Top 5 Job Categories That Demand the Most Data Science Experts,” National Review’s Steven Horwitz points out that the engineering profession has become so highly specialized that it now requires an average of two engineering degrees in order to gain the right skills for any field.

The problem, Horwitz writes, is that there is no “gold standard” for how a computer science major should conduct its research. 

It’s not hard to see why. 

“If you have a lot of engineers and you think you’re going to be a data scientist,” Horwitz says, “you’re probably going to make mistakes.” 

“The field is a bit too small,” says Dr. Robert Litt, who heads up the program at the University of Washington’s Data Science and Machine Learning Laboratory. 

There are plenty of data scientists, Litt says, who don’t think that a computer scientist should be a computer programmer. 

In fact, he points out, the vast majority of data science jobs in the United States are “nontechnical” jobs. 

Litt says the “data scientist” job requires a lot more than a PhD. For one thing, it requires a very deep knowledge of machine learning, which, like most science, is largely about data. 

Also, Latt says, computer science degrees can’t be combined with a career in medicine or law, because the latter requires more degrees. 

One major obstacle to making a career out of computer science, Lett says, is the lack of an “industry-standard” degree. 

That means that a person who wants to work in a computer-science field can’t just get a bachelor’s degree, Lipp says. 

Instead, he suggests a master’s degree in computer science or a doctorate. 

If that’s not possible for you, then a career as a data analyst might be just what you need. 

Data scientist job opportunities are scarce. 

And because of that, Horitz and Litt say, it’s important to understand exactly what it takes to be an engineer in the data science field. 

Here are five key skills to know to become a data science engineer: 1. 

You can’t have an “engineer” job and not have a data geek. 

Horny data scientist?

You’re not alone. 

According to the National Center for Education Statistics, about 17% of American adults have a bachelor degree or higher in computer engineering. 

The number of data nerds in the U.S. has grown to about 6.3 million, according to the Pew Research Center. 

A survey by The Wall Street Journal found that nearly two-thirds of all U.K. adults who had a computer engineer degree were female. 

Of those women, a majority (60%) said they had no desire to become data scientists. 

So what is a data nerd? 

“Data scientists are engineers that have a love for data,” Litt tells National Review. 

These are the data nerds who are the backbone of companies like Twitter, Airbnb, Uber, and Netflix. 

They’re also the ones who build and maintain complex data-heavy applications that provide value to users. 

But, as Litt notes, there are plenty who aren’t so obsessed with data. 

 “There are lots of people who are really interested in engineering, but they don’t really have an interest in data,” he says.

“That’s where the data geek comes in.” 

Data scientists can’t do the work that engineers can, because it requires more math, Lott says.

So, Lutt is quick to point out that, while a data engineer is an engineer, he’s not a data physicist. 

When it comes to coding, Latto says, there’s no one type of code. 

However, there is a type of coding that a data specialist can learn and apply to solve problems. 

Code analysis is when programmers are able to create “code analysis” engines that can automatically parse data to make sure that certain things are being done right. 

Using code analysis, Latta says, a data person can “make decisions about how data is being fed into their system, what it should look like, and what it shouldn’t look like.” 

Code analyzers like those found in Uber’s Dataflow and Google’s BigQuery are used to help data engineers analyze data.

Latto also says that, like a data programmer, a code analyst should be familiar with programming languages like Python, Ruby, and JavaScript. 

Additionally, Latti points out data scientists should have “a knack for reading data and analyzing it to make the right decisions.” 

2. 

No one really needs a PhD in data science. 

What if you do? 

Not all data scientists are computer science majors, Litz says.

But some are. 

Indeed, a number of people have a Ph.

D. in the field