Although we find ourselves in unprecedented times of uncertainty, current events have shown just how valuable the fields of Data Science and Computer Science truly are. Technologies — like the Johns Hopkins dashboard, contact tracing, and data analytics — compose the “virtual front lines” of our attack on the pandemic and continuously prove to be driving sources of change. However one question still remains: Exactly how valuable are these fields?

一个 lthough我们以前所未有的不确定的时候发现自己，目前的事件表明，多么的有价值数据科学和计算机科学领域确实是。 诸如Johns Hopkins仪表板 ， 联系人跟踪和数据分析之类的技术构成了我们对大流行的攻击的“虚拟前线”，并不断被证明是推动变化的源头。 然而，仍然存在一个问题：这些领域究竟有多有价值 ？

In this article we will take a snapshot of where Data Science is in 2020 and take a deep dive into where salaries and other forms of compensation stand.

在本文中，我们将简要介绍2020年数据科学的现状，并深入探讨薪资和其他形式的薪酬水平。

数据科学家的薪水是多少？ (What is the Salary of a Data Scientist?)

To answer this, let’s move on over and check out Payscale: a salary insights platform. Taking a look, we can see that it reports that the current median salary for a Data Scientist is $95,973 with a range spanning from 66k to 134k.

为了回答这个问题，让我们继续并检查Payscale ：一个薪资洞察平台。 看一下，我们可以看到它报告说，数据科学家的当前中位数工资为95,973美元 ，范围从66k到134k。

However, that’s not the whole picture. If we look closely, we also see that Payscale reports an average bonus of $9000 along with $976 — $25k in profit sharing and $1k — $10k in commission.

但是，这还不是全部。 如果我们仔细观察，我们还可以看到Payscale报告的平均奖金 为9000美元，以及976美元( 2.5 万美元的利润分成和1000美元-1万美元的佣金)。

体验如何影响薪酬？ (How Does Experience Affect Pay?)

As you’d expect, the amount of experience does have a direct correlation to pay. Take a look at this graph for a quick breakdown!

正如您所期望的那样，经验的数量确实有直接的相关性。 快看一下这张图吧！

The key takeaway can be deduced from the binned years of experience. What pops out is the fact that the median salary can be met fairly quickly: according to this graph, within the first five years, you can be making more than the median salary of a Data Scientist!

关键要点可以从多年的经验推论得出。 突然出现的事实是，工资中位数可以很快达到：根据此图，在头五年内，您可以获得的收入将超过数据科学家的工资中位数！

位置呢？ (What About Location?)

Moving on, let’s take a look at how location affects salary:

继续，让我们看一下地理位置如何影响薪资：

As expected, silicon valley is once again raking in the big bucks. However, I wouldn’t jump to conclusions too quick; these salaries are highly correlated to the cost of living within the region.

不出所料，硅谷再次赚了大钱。 但是，我不会太快得出结论。 这些工资与该地区的生活成本高度相关。

For example, even though working in San Francisco nets a~30 percent salary increase, you could still be making less than someone working in Atlanta after accounting for CoL (Cost of Living). Let’s look a bit deeper into this: using this CoL calculator, we can see just how big of a discrepancy there is between San Francisco and Atlanta:

例如，即使在旧金山工作净增加了30％的薪水，但考虑到CoL(生活费用)后，您的收入仍然可能比在亚特兰大工作的人要少。 让我们更深入地了解一下：使用此CoL计算器 ，我们可以看到旧金山和亚特兰大之间的差异有多大：

Atlanta is significantly cheaper when it comes to every department! Just to show you how significant this is, let’s take a look at the average national rent: $1,468. This comes out to the average monthly rent being $1380 in Atlanta and a whopping $3392 in San Francisco. In all, this nets an annual difference of $24,144! This still does not account for other fees like utilities and groceries; both of which vary significantly between the two cities. So before you take that six figure salary, make sure it actually is a six figure salary!

每个部门的亚特兰大便宜得多！ 为了说明这有多重要，让我们看一下平均租金： $ 1,468 。 这样算来 ， 亚特兰大的平均月租金为1380 美元 ， 旧金山的平均月租金为3392美元 。 总共，每年的净差额为24,144美元！ 这仍然不包括其他费用，例如水电费和杂货； 两者在两个城市之间差异很大。 因此，在您获得六位数的薪水之前，请确保它实际上 是六位数的薪水！

与相关薪资比较 (Comparing to Related Salaries)

So now that we have a good understanding of how much a Data Scientist makes, how does it stack up to other Computer Science professions?

因此，现在我们对数据科学家的收入有了很好的了解，它如何与其他计算机科学专业相结合？

This list figure gives us a good snapshot of the ranges similar career salaries fall into. The most surprising thing to me personally is that the median salary for a Data Scientist is over $10,000 more than a Senior Software Engineer! Likewise, the median salary of a Data Scientist is significantly greater than every profession listed — crazy right?!

这个清单数字使我们可以很好地了解类似的职业薪资范围。 对我个人而言，最令人惊讶的是，数据科学家的薪水比高级软件工程师的薪水高出10,000美元！ 同样，数据科学家的中位数工资显着高于列出的每个职业-疯狂吧？

For a more in depth look into the salaries of different positions, let’s dive into the Stack Overflow Coding Salary Calculator. As stated within the page, the calculator “is based on the comprehensive data from the Stack Overflow Developer Survey, and this large, extensive survey data allows us to build an accurate model that reflects trends in how coding work is being compensated around the world.”

要更深入地了解不同职位的薪水，让我们深入研究Stack Overflow Coding Salary Calculator 。 如该页面中所述，“计算器”基于来自Stack Overflow开发人员调查的综合数据，而这一庞大而又广泛的调查数据使我们能够建立一个准确的模型，以反映世界各地如何补偿编码工作的趋势。 ”

The thing that pops out immediately is the placement of Data Engineer and Data Scientist as the top three paying developer roles in every country the data was collected from. When looking at the countries, you can notice how much different roles and their compensation vary depending on region; for example, take a look at the ranking of QA or test developers amongst the different countries. The fact that the data roles are so consistently ranked is an amazing sign. It shows that all countries require and value data scientists to the same extent!

突然出现的事情是，数据工程师和数据科学家在每个收集数据的国家/地区中排名前三位，都是付费开发人员。 在查看国家/地区时，您会注意到不同的角色及其薪酬因地区而异。 例如，请查看不同国家/地区的质量检查或测试开发人员的排名。 数据角色如此稳定地排名的事实是一个了不起的迹象。 它表明，所有国家都在同等程度上要求和重视数据科学家！

However, there’s a catch. Before you go off and think that the best way to make money is becoming a data scientist check this excerpt the stack overflow researcher made in the calculator:

但是，有一个陷阱。 在您开始思考并认为赚钱的最佳方法是成为数据科学家之前，请检查以下摘录，这是计算器产生的堆栈溢出研究人员：

[W]e have evidence here that high salaries for data scientists and data engineers can be accounted for by high education and high experience levels alone. Data scientists are highly paid, but not more so than a similarly educated developer doing other kinds of work. (Both bachelor’s degrees and even higher degrees are associated with significantly increased pay for people who code.) Over the past several years, data science and data engineering work have been moving away from an extreme outlier position into the mainstream of software work.

[这里]有证据表明，仅通过高学历和高经验水平就能为数据科学家和数据工程师带来高薪。 数据科学家的薪水很高，但比从事其他工作的受过类似教育的开发人员的薪水更高。 (学士学位甚至更高的学位都与编码人员的薪水显着增加有关。)在过去的几年中，数据科学和数据工程工作已经从极端的局面转移到软件工作的主流。

In short, although data engineers and data scientists do make the most money, a major factory that plays into the salaries is higher education and experience. As noted above, the individuals who tend to pick up data roles are much more likely to have degrees and years of experience.

简而言之，尽管数据工程师和数据科学家确实赚钱最多，但发挥薪资的主要工厂是高等教育和经验。 如上所述，倾向于担任数据角色的个人更有可能拥有学位和多年的经验。

结论 (Conclusion)

So, how much is a data scientist worth in 2020? Well, if you want a straight answer ~$100,000 on average.

那么，2020年数据科学家的身价是多少？ 好吧，如果您想直接回答，平均费用为$ 100,000。

BUT before you go off and start applying to data scientist roles chasing money, let me highlight something. As stated in the developer calculator above, data scientists do not make significantly more than a similarly educated developer.

但是，在您开始申请数据科学家职位之前，让我重点介绍一下。 如上面的开发人员计算器所述，数据科学家的收入远不及受过类似教育的开发人员。

It is important that you come to the realization that, more than the money you make when you pick up the job, you should value the amount of enjoyment you get from the role. At the end of the day, similarly educated and experienced developers will make fairly identical salaries.

重要的是，您必须认识到，除了担任工作所赚的钱以外，您还应该珍视从角色中获得的乐趣。 最终，受过类似教育和有经验的开发人员将获得完全相同的薪水。

Find the role you’re passionate about and the money will follow. Don’t flip that around and chase the money hoping to find your passion!

找到您热衷的角色，金钱就会随之而来。 不要四处乱逛，追逐金钱，希望找到自己的激情！