David Robinson, a data scientist, has said the following quotes:

数据科学家David Robinson曾说过以下话：

“When you’ve written the same code 3 times, write a function.”

“当您编写了3次相同的代码时，请编写一个函数。”

“When you’ve given the same in-person advice 3 times, write a blog post.”

“当您两次给出相同的面对面建议时，请写一篇博客文章。”

The first quote is something you should adopt soon, but the focus (literally) for this post is the second quote. I wrote an article recently sharing some tips from my data science journey. In this article, I want to share with you the overall theme that I have been giving advice on since that post, focus.

第一个引号是您应该很快采用的，但是本文的重点(从字面上看)是第二个引号。 我最近写了一篇文章， 分享了我在数据科学历程中的一些技巧 。 在本文中，我想与您分享自从发表这篇文章以来，我一直在提供建议的总体主题。

为什么重点很重要？ (Why focus is important?)

If you were to follow the strands on this spider web, you could end up in many different intersection points.

如果您要跟踪此蜘蛛网上的子线，则可能会遇到许多不同的交点。

You could also take multiple paths to the same intersection point. But there is an optimal path. A shorter path. This is true of the data science field also. Just the number of subfields alone is vast. Even more so if you include the subject knowledge you need for projects if they are not in the same domain. If can quickly feel overwhelming…

您也可以采用多条路径到达相同的交点。 但是有一条最佳的道路。 更短的路径。 数据科学领域也是如此。 仅子域的数量是巨大的。 更重要的是，如果您包含的主题知识不属于同一领域，那么您就需要这些项目。 如果可以很快感到不知所措...

It took me 2.5 years to land my data science role. If you haven’t read the prior article, here is some quick background on my situation:

我花了2.5年的时间才能获得数据科学职位。 如果您还没有阅读上一篇文章，请快速了解我的情况：

1. I am a husband and father to a toddler.
   我是一个小孩的丈夫和父亲。
2. I was a high school teacher with an hour commute in each direction by car.
   我是一名高中老师，每个方向的通勤时间均为一个小时。
3. I only had an hour or so a day dedicated to data science since my wife supported me in this career change.
   自从妻子支持我从事这项职业以来，我只有一个小时左右的时间致力于数据科学。

I didn’t focus at the beginning. I started with an overview foundation since I didn’t have much of a programming background. I would still recommend this if you have no background in math and/or coding. The problem came afterward when everything about the field was so fascinating I leaped at everything I could interact with. But it prevented me from mastering anything, leading me into that classic saying…

一开始我没有集中精力。 我从概述基础开始，因为我没有太多的编程背景。 如果您没有数学和/或编码的背景，我仍然会建议这样做。 随后，当有关该领域的所有事情都如此吸引人时，我就跳下了我可以与之互动的一切的问题。 但这阻止了我精通一切，使我陷入了那句经典的话……

“Jack of all trades, master of none.”

“万事通，无精打采。”

Eventually, I felt incredibly overwhelmed. From that, there was a time when I shut down and didn’t practice anything for a few weeks.

最终，我感到难以置信。 从那时起，有一段时间我关闭了并且几周没有练习任何东西。

那么如何避免我的错误呢？ (So how can you avoid my mistake?)

There are a couple of approaches you could take and I should have considered sooner:

您可以采取几种方法，我应该早点考虑：

1. Focus on a particular branch of data science such as natural language processing or data visualization.
   专注于数据科学的特定分支，例如自然语言处理或数据可视化。
2. Focus on a domain and sculpt your data science skills around projects in that domain.
   专注于某个领域，并围绕该领域的项目雕刻您的数据科学技能。

After I got some help to get out of my rut, I took the second approach. Leveraging my educational background, I focused on solving problems related to the education field from the perspective of a teacher. This led me to:

在获得帮助以摆脱困境后，我采取了第二种方法。 利用我的教育背景，我专注于从老师的角度解决与教育领域有关的问题。 这导致我：

1. Influencing a hiring decision based on the academic needs of students.
   根据学生的学术需求影响招聘决定。
2. Created an overview of my school’s performance in a concise report.
   在简明的报告中概述了我学校的表现。

3. Using a Bayesian version of a T-test to determine if my review lesson improved the student’s understanding and by how much.

   使用贝叶斯T检验确定我的复习课是否提高了学生的理解力以及提高了多少。

4. Analyzing state exam questions to guide curriculum decisions.
   分析州考试题以指导课程决策。

These projects I put on my LinkedIn profile. They got the attention of people I did not expect. It got the attention of the outside school consultant who ended up providing a lot of future help. It got the attention of a Facebook recruiter for a related data science/education position with a starting salary above $130,000. Discussing my experience with these projects got me past the first round of interviews easily.

这些项目我放在我的LinkedIn个人资料中。 他们引起了我意料之外的人们的注意。 引起了外部学校顾问的注意，他们最终提供了很多未来的帮助。 它吸引了一位Facebook招聘人员的注意，该招聘人员的相关数据科学/教育职位的起薪超过13万美元。 讨论我在这些项目中的经验使我轻松通过了第一轮采访。

My rate of getting interviews and getting further in the rounds soon improved since I became more focused. Again, given my situation, it wasn’t the fastest, but it was a vast improvement compared to my previous rate. Each interview improved how I presented myself. Until eventually…

自从我变得更加专注之后，我获得面试和进一步进步的速度很快就提高了。 同样，鉴于我的情况，它不是最快的，但是与我以前的速度相比，这是一个巨大的进步。 每次采访都改善了我的自我介绍。 直到最后……

I succeeded! I landed my dream role and broke into the data science field!

我成功了！ 我找到了自己梦dream以求的角色，并闯入了数据科学领域！

At the time of writing this, it has been just shy of three months since this new career started and it has been incredible! The people I work with are amazing, I get constant feedback, my work is having an immediate and/or future impact, and I am getting praised for it (as a teacher you don’t get that often so it is important to me…and also I am a kid at heart).

在撰写本文时，距这个新职业生涯还不到三个月，这简直令人难以置信！ 与我共事的人很棒，我得到不断的反馈，我的工作具有立竿见影和/或未来的影响，我为此而受到赞誉(作为老师，您很少得到这样的帮助，所以对我来说很重要……)而且我还是个内心的孩子)。

If you are still hunting for your career just know it isn’t impossible. You can do it! Just focus on what you want to do in this field as soon as possible. If you are still experimenting a bit that is ok. But I would recommend doing it quickly if possible. If you are a parent or have a similar situation to me do know it will take longer, but you will get there.

如果您仍在寻找自己的职业，那就知道那并非不可能。 你能行的！ 请尽快专注于您要在该领域中要做的事情。 如果您仍在尝试，那还可以。 但是我建议尽可能快地这样做。 如果您是父母或与我有类似的情况，请知道这将花费更长的时间，但是您会到达那里。

When you do get there, you will reflect on your journey up to that point. You will review the good and bad of it all. Finally, you will turn toward the future of your new career, and be amped to get started!

当您到达那里时，您将反思到那时的旅程。 您将回顾所有优点和缺点。 最终，您将转向新职业的未来，并为入门做好准备！

Thanks for reading! If you found this post helpful and you haven’t checked out some of the tips from my journey, you can read about them below:

谢谢阅读！ 如果您发现这篇文章很有帮助，但还没有从我的旅程中找到一些技巧，则可以在下面阅读有关它们的信息：

Also if you are entering the field with a math background and feel you need help organizing a learning plan, check out my recommendations in this article below:

另外，如果您以数学背景进入该领域，并且认为需要帮助组织学习计划，请在下面的本文中查看我的建议：

You can follow me here or connect with me on Linkedin and Twitter. Open to DM’s on Twitter.

您可以在这里关注我，也可以通过Linkedin和Twitter与我联系。 在Twitter上打开DM。

Until next time,

直到下一次，

John DeJesus

约翰·德耶稣