好消息轮询
There’s good news if you’ve been thinking of getting into the field of data science or have been looking for your perfect position in the past few months. It seems hiring is on the rise with data science positions and related positions across the board coming back strong during the beginning of the third quarter.
如果您正在考虑进入数据科学领域，或者在过去几个月中一直在寻找自己的理想位置，那么这将是一个好消息。 在第三季度初，随着数据科学职位和相关职位全面恢复强劲，招聘人数似乎正在上升。
Talk to data scientists, however, and you might get a completely different picture. So how can it be both easier and harder to find data science jobs at the same time? It’s a matter of data presentation.
但是，与数据科学家交谈，您可能会得到完全不同的印象。 那么，如何同时又容易又困难地找到数据科学工作呢？ 这是数据表示的问题。
According to the numbers posted on various job sites since the beginning of the year, you see the predictable plummet of job postings around the height of COVID shut down — albeit at a slower pace than average in the job sector. By June, those postings rose sharply, peaking just before July but continuing to show steady promise.
根据自今年年初以来在各个工作站点上发布的数字，您会发现，在COVID高度附近，可预见的工作发布骤然下降-尽管其速度低于工作部门的平均水平 。 到6月，这些职位急剧上升，在7月之前达到顶峰，但继续显示出稳定的前景。
With the general unemployment rate climbing as high as 16% by May of 2020 and as many as 60% of employers reducing job postings according to sources in April, even the number one hottest job was beginning to worry.
消息来源称，到2020年5月，总体失业率攀升至16％，多达60％的雇主减少了职位发布，即使是最热门的工作也开始令人担忧。
That’s changed. Overall, the US has added back roughly 4.8 million jobs, with plenty of those covering the field of data science. Job seekers should be rejoicing. As all data scientists are aware, however, numbers don’t always give the full picture.
改变了。 总体而言，美国增加了大约480万个工作岗位，其中很多覆盖了数据科学领域。 求职者应该很高兴。 但是，正如所有数据科学家都知道的那样，数字并不总能提供全部信息。
These jobs should be easier than ever to snag, but anecdotal evidence paints a far different picture. Out of work data scientists and recent graduates are having a harder time pinning down jobs and hearing back from employers. There could be a few reasons for this.
这些工作应该比以往任何时候都容易，但轶事证据却描绘出截然不同的景象。 失业数据科学家和应届毕业生很难确定工作并听取雇主的反馈。 可能有一些原因。
One could be the recent round of layoffs in prominent startups. Uber closed its AI doors, laying off more employees than Lyft, Groupon, and Airbnb combined. Startups located in the hospitality and event industries ground operations to a halt with Eventbrite laying off 45% of employees or Flywheel Sports laying off nearly everyone.
一个可能是最近一轮的 知名初创公司 裁员 。 Uber关闭了AI门，裁员人数超过Lyft，Groupon和Airbnb的总和。 接待和活动行业的初创公司停止运营，Eventbrite裁员45％，Flywheel Sports裁员。
While many of these startups are planning a comeback, these layoffs hurt the overall data science job market. As startups begin to raise the kind of capital they needed to maintain growth, or more relevant startups hit the market, this could change.
尽管这些初创公司中有许多正在计划卷土重来，但这些裁员伤害了整个数据科学工作市场。 随着初创企业开始筹集维持增长所需的资本，或者更多相关的初创企业进入市场，这种情况可能会改变。
Companies during this time of disruption could be waiting for unicorn candidates to shore up security and in a belief that the talent pool has widened. While many companies know that freezing hiring in technology could hurt them, they may be reticent to take chances on new talent.
在这段混乱的时期，公司可能会等待独角兽候选人提高安全性，并相信人才库已经扩大。 尽管许多公司都知道冻结招聘技术可能会伤害他们，但他们可能不愿抓住机会吸引新人才。
Instead, believing that the pool has widened due to recent cutbacks from other fields, companies may be taking longer to find the right candidate. They could also be waiting for budget freezes to end or a sign that the disruption is nearly over.
取而代之的是，由于最近其他领域的裁员，他们认为人才库已经扩大，因此公司可能需要更长的时间才能找到合适的人选。 他们也可能在等待预算冻结结束或迹象表明中断即将结束。
Google, Apple, Amazon, Netflix, and Google haven’t stopped hiring. In fact, as COVID continued to disrupt the economy, these companies have invested aggressively in new talent, looking for new market opportunities and widening their pool of influence.
Google，Apple，Amazon，Netflix和Google都没有停止招聘 。 实际上，随着COVID继续扰乱经济，这些公司已经在新人才上进行了积极投资，以寻找新的市场机会并扩大影响力。
Amazon added over 40,000 jobs in data science at the height of the crisis in April while Facebook and Google followed suit. With startups closing or freezing budgets, now is the time to pick off top talent.
在四月危机最严重的时候，亚马逊增加了40,000多个数据科学工作，而Facebook和Google紧随其后。 随着初创企业关闭或冻结预算，现在是时候选拔顶尖人才了。
For data science talent, that means more jobs but fewer opportunities as these giants funnel positions into the machine, creating both demand and restriction.
对于数据科学人才来说，这意味着更多的工作，但机会更少，因为这些巨头将职位转移到机器中，从而产生了需求和限制。
Data scientists need to be strategic to make these numbers work for them.
数据科学家必须具有策略性，以使这些数字对他们有用。
Network where the jobs are — Healthcare is ramping up both startup funding and hiring. Biotech is still racing to find the vaccine for COVID. If you aren’t into FAANG, going where the demand is could be your key.
在工作中找到网络 – 医疗保健部门正在增加启动资金和招聘。 生物技术公司仍在竞相寻找用于COVID的疫苗。 如果您不喜欢FAANG，那么去需求的地方可能就是您的关键。
Stay positive — August is a slow hiring month anyway with vacations and HR reluctant to get moving at the end of summer. Use this time to uplevel your skills or hone your connections.
保持乐观 —八月是一个缓慢的招聘月份，假期和人力资源部门不愿在夏季结束时搬家。 利用这段时间来提升您的技能或磨练您的人际关系 。
Join a community — Take advantage of the networking, community wisdom, and career tips from your local Data Science meetup groups or find a virtual option. There’s strength in numbers, and those numbers can help keep you motivated.
加入社区 -利用本地数据科学聚会小组的网络联系，社区智慧和职业提示，或找到一个虚拟的选择。 数字有优势，这些数字可以帮助您保持动力。
Finding your data science job can and will happen. Just because the data tells different stories doesn’t mean you can’t connect with employers and find your position. Data is the new gold standard, the new oil, whatever metaphor you want for the fourth industrial revolution, so the right job is there. Be patient, and stay positive.
找到您的数据科学工作可能并且将会发生。 仅仅因为数据讲述了不同的故事，并不意味着您无法与雇主联系并找到自己的职位。 数据是新的黄金标准，新的石油，无论您想要第四次工业革命是什么样的隐喻，因此正确的工作就在那里。 要有耐心，保持积极。
Original post here.
原始帖子在这里。
Read more data science articles on OpenDataScience.com, including tutorials and guides from beginner to advanced levels! Subscribe to our weekly newsletter here and receive the latest news every Thursday.
在 OpenDataScience.com 上阅读更多数据科学文章 ，包括从初学者到高级的教程和指南！ 在此处订阅我们的每周新闻， 并在每个星期四接收最新新闻。
翻译自: https://medium.com/@ODSC/looking-for-data-science-jobs-in-the-pandemic-good-news-and-not-so-good-news-1add9367c861
好消息轮询
