意见 (Opinion)

目录 (Table of Contents)

1. Introduction
   介绍
2. Salary and Growth
   薪资与增长
3. Summary
   摘要

介绍 (Introduction)

In the past five years, data science salary cumulative growth has varied between 12% in the United States, according to Glassdoor’s job market report [2]. Between those five years, there have been certain months of significant increase and decrease. In this article, I will outline the key metrics that occur at certain months and years of these five years, including median base pay, cumulative growth, and year-over-year growth. Somewhat similar careers, like software engineering, have seen steady inclines over the same period, so it is important to note the volatility of data science salaries.

根据Glassdoor的就业市场报告[2]，在过去的五年中，美国数据科学专业的薪资累积增长在12％之间变化。 在这五年之间，有几个月出现了明显的增加和减少。 在本文中，我将概述这五年中某些月份和年份发生的关键指标，包括基本工资中位数，累计增长和逐年增长。 某些类似的职业，例如软件工程，在同一时期出现了稳定的增长趋势，因此，重要的是要注意数据科学人员薪资的波动性。

I will speculate as to why there is either an increase or decrease in growth along with its respective median base salary for each significant period of time. There are many reasons as to why these changes have occurred, and it is interesting to look at the differences between months and years for data science salary, spanning over $10,000 total. If you would like to know more salary information on similar positions like data analyst and software engineer, you can refer to the same Glassdoor job market report by following the link at the end of this article.

我将推测为什么在每个重要的时期内，增长率及其相应的基本工资中位数都会增加或减少。 发生这些变化的原因有很多，有趣的是看看数据科学月薪和年薪之间的差异，总额超过10,000美元。 如果您想了解有关数据分析师和软件工程师等类似职位的更多薪资信息，可以通过以下文章末尾的链接引用同一份Glassdoor工作市场报告。

薪资与增长 (Salary and Growth)

I will be discussing the key metrics over the rise and fall and rise again of data science salaries below.

我将在下面讨论数据科学薪资的起伏和上升趋势的关键指标。

上升 (Rise)

June 2015

2015年6月

The initial rise of the five year period is June of 2015. This month recorded a median base salary of $95,798, with a cumulative growth of 6.2%. There could be several reasons to explain this growth. While it is not recorded, I can speculate on what has caused this change in cumulative pay growth.

五年期间的最初增长是2015年6月。本月基本工资中位数为$ 95,798 ，累计增长6.2％ 。 可能有几个原因可以解释这种增长。 虽然没有记录，但我可以推测是什么原因导致了累积工资增长的这种变化。

I would suggest that the spike in growth is from companies realizing how powerful and popular this career in data science is. Once companies hire more and more data scientists, it becomes more competitive not only for the applicant, but for the employer as well. I am considering that in 2015, in this case, data science is well-established, and applicants feel more confident in demanding a higher salary, as well as companies allocating more of their budget to data science careers after seeing or hearing about wide success with this position on businesses.

我建议增长的高峰来自公司，他们意识到数据科学事业的强大和流行。 一旦公司聘请了越来越多的数据科学家，它不仅对申请者而且对雇主都更具竞争力。 我考虑的是，在这种情况下，2015年的数据科学已经建立了良好的基础，申请人对要求更高的薪水更有信心，而且在看到或听到了广泛的成功经验之后，公司也将更多预算分配给数据科学职业这个职位对企业。

In some cases, you could argue that one data scientist could perform the function of two analysts from the automation of common processes with programming language like Python, so why not pay one person a little more instead of having two people cost your business even more in the long run? Of course, all companies are different in some ways, along with their respective roles, so this could be beneficial or detrimental. Additionally, data analysts can sometimes have considerably different tasks, processes, and impacts.

在某些情况下，您可能会争辩说，一位数据科学家可以使用像Python这样的编程语言来实现通用流程的自动化，从而执行两位分析师的职能，因此，为什么不花一个人多付钱，而不是让两个人花更多的钱在您的企业中从长远来看？ 当然，所有公司在某些方面以及他们各自的角色上都是不同的，因此这可能是有益的或有害的。 此外，数据分析师有时可能会有截然不同的任务，流程和影响。

Once again, here are the metrics for the first rise:

再一次，这是第一次上升的指标：

Rise of June 2015median base salary: $95,798cumulative growth: 6.2%

秋季 (Fall)

June 2016

2016年六月

Once companies hired their first data scientist, they sought out to hire more.

一旦公司聘请了第一位数据科学家，他们便寻求聘用更多的人。

Perhaps this trend meant that they already had a senior data scientist and the next logical choice was to look for a junior data scientist that could be acquired for a smaller salary.

也许这种趋势意味着他们已经有一位高级数据科学家，下一个合乎逻辑的选择是寻找一个初级的数据科学家，可以以较低的薪水获得它。

This fall in June of 2016 was considerably substantial in that the median base salary dropped to $88,649 with a cumulative growth of -1.7% and a year-over-year growth of -7.5%. Yes, those last two statistics were negative. While I do not know for certain the cause of this significant drop in pay, I do know that there were going to be better months and years ahead. As a data scientist myself, I would create a dataset to isolate key, significant features like the following:

2016年6月的这个秋天相当可观，基本工资中位数降至88,649美元 ，累计增长-1.7％ ，同比增长-7.5％ 。 是的，最后两个统计数据均为负数。 虽然我不确定工资大幅下降的原因，但我确实知道未来几个月和几年会更好。 作为数据科学家本人，我将创建一个数据集以隔离关键的重要功能，例如：

• location
  位置
• demographic
  人口统计
• spread of junior and senior roles
  初级和高级职位的传播
• split of data science and machine learning positions
  数据科学和机器学习职位的划分
• range of salary expanding
  薪资范围扩大
• negative press
  负面新闻
• employee reviews
  员工评价
• budget cuts
  削减预算
• budget allocations
  预算拨款
• errors in reporting pay
  工资报错
• current events
  现在发生的事
• inflation
  通货膨胀
• etc.
  等等

As you can see, there are several different ways of dissecting this decrease in pay. Luckily, the fall did not last long, and a huge rise would top that initial rise. Here are those metrics highlighted once more:

如您所见，有几种不同的方法可以剖析这种薪资下降的情况。 幸运的是，这种下降并没有持续很长时间，而且大幅上升将超过最初的上升。 这些指标再次突出显示：

Fall of June 2016median base salary: $88,649cumulative growth: -1.7%year-over-year growth: -7.5%

再次上升 (Rise Again)

June 2020

2020年6月

It took a few years to see this rise again, which occurred recently in June 2020. Perhaps with COVID-19, tech roles became of more focus as employees demanded to work from home, or were required to. Customer-facing roles perhaps declined, as many new positions would need to be performed individually at home, over a video conferencing platform. Nearly $100,000, the median base pay for data scientists in this month was $99,674 with a cumulative growth of 10.5% and a year-over-year growth of 5.5%. This rise again is of course great news for data scientists. If you have not noticed yet, it is important to note that all of these key dates have been in the month of June of their respective years, perhaps it is just a coincidence, but it would be interesting to know why this trend and pattern occurred.

几年后才再次出现这种情况，这种情况最近发生在2020年6月。也许是在COVID-19的情况下，随着员工要求在家中工作或被要求在家工作，技术角色变得更加重要。 面向客户的角色可能会下降，因为需要通过视频会议平台在家中单独执行许多新职位。 近十万美元，本月数据科学家的基本薪资中位数为$ 99,674 ，累计增长10.5％ ，同比增长5.5％ 。 对于数据科学家来说，再次上升当然是个好消息。 如果您尚未注意到，则需要注意的是，所有这些关键日期都是在各自年份的6月，也许这只是一个巧合，但是了解为什么会出现这种趋势和模式会很有趣。 。

The summarized information is here for the rise again:

摘要信息再次出现在这里：

Rise Again of June 2020median base salary: $99,674cumulative growth: 10.5%year-over-year growth: 5.5%

摘要 (Summary)

For easy viewing, the chart above summarizes the key dates along with their respective metrics of median base salary, cumulative growth, and year-over-year growth. This chart was made in Google Data Studio and covers the key points in time discussed in this article. If you would like to see a more detailed time series chart with more months and years including not only the data science statistics, but other technology position statistics, follow the link from Glassdoor in the references section below.

为了便于查看，上表总结了关键日期及其各自的基本工资中位数，累积增长和逐年增长指标。 该图表是在Google Data Studio中制作的，涵盖了本文中讨论的关键时间点。 如果您想查看更详细的时序图，包括更多月和几年的时间，不仅包括数据科学统计信息，还包括其他技术位置统计信息，请按照下面参考部分中的Glassdoor链接。

As for the future of data science salary, it could be tricky to predict with the pandemic occurring, and companies that were once steady, are now volatile in themselves. Perhaps, data science pay will rise with more tech companies performing better, or the salary will decline as more and more companies, in general, are declining. Additionally, data science positions could soon offer more or less pay based on their split in specific requirements for the position. For example, a data scientist role in 2025 could reduce to a median base salary of $95,000, while a machine learning engineer role could increase to $105,000. This change could result in response to companies needing to rely more on the deployment of models and less face-to-face interactions.

至于数据科学领域的薪资前景，要预测这种大流行的发生可能会很棘手，而且曾经很稳定的公司现在已经变得不稳定。 也许，随着越来越多的科技公司表现更好，数据科学的薪资将会增加，或者随着越来越多的公司总体而言薪水的下降，薪水将会下降。 此外，根据数据科学职位的具体要求，他们很快就会提供或多或少的报酬。 例如，到2025年，数据科学家的角色的基本年薪中位数可降低至95,000美元，而机器学习工程师的角色的中位数则可增至105,000美元。 这种变化可能会导致企业需要更多地依赖模型的部署和更少的面对面交互。

In this article, we discussed the rise, fall, and rise again of data science salaries. There are several reasons for these changes in pay growth over the past five years. Feel free to comment down below on why you think this median pay changes so frequently. Keep in mind, this highly changing trend was not the same for similar roles in technology like software engineering, systems engineering, and web developer.

在本文中，我们讨论了数据科学人员薪水的上升，下降和再次上升。 在过去五年中，薪资增长发生这些变化的原因有很多。 请随意在下方评论为什么您认为中位数工资变化如此频繁。 请记住，对于像软件工程，系统工程和Web开发人员这样的技术中的类似角色，这种高度变化的趋势并不相同。

I hope you found my article useful and interesting. Thank you for reading my article!

希望您发现我的文章有用且有趣。 感谢您阅读我的文章！