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

數據科學家David Robinson曾說過以下話：

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

“當您編寫了3次相同的代碼時，請編寫一個函數。”

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

“當您兩次給出相同的面對面建議時，請寫一篇博客文章。”

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.

第一個引號是您應該很快采用的，但是本文的重點(從字面上看)是第二個引號。 我最近寫了一篇文章， 分享了我在數據科學歷程中的一些技巧 。 在本文中，我想與您分享自從發表這篇文章以來，我一直在提供建議的總體主題。

為什么重點很重要？ (Why focus is important?)

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

如果您要跟蹤此蜘蛛網上的子線，則可能會遇到許多不同的交點。

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…

您也可以采用多條路徑到達相同的交點。 但是有一條最佳的道路。 更短的路徑。 數據科學領域也是如此。 僅子域的數量是巨大的。 更重要的是，如果您包含的主題知識不屬于同一領域，那么您就需要這些項目。 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年的時間才能獲得數據科學職位。 如果您還沒有閱讀上一篇文章，請快速了解我的情況：

1. I am a husband and father to a toddler.
   我是一個小孩的丈夫和父親。
2. I was a high school teacher with an hour commute in each direction by car.
   我是一名高中老師，每個方向的通勤時間均為一個小時。
3. I only had an hour or so a day dedicated to data science since my wife supported me in this career change.
   自從妻子支持我從事這項職業以來，我只有一個小時左右的時間致力于數據科學。

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…

一開始我沒有集中精力。 我從概述基礎開始，因為我沒有太多的編程背景。 如果您沒有數學和/或編碼的背景，我仍然會建議這樣做。 隨后，當有關該領域的所有事情都如此吸引人時，我就跳下了我可以與之互動的一切的問題。 但這阻止了我精通一切，使我陷入了那句經典的話……

“Jack of all trades, master of none.”

“萬事通，無精打采。”

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

最終，我感到難以置信。 從那時起，有一段時間我關閉了并且幾周沒有練習任何東西。

那么如何避免我的錯誤呢？ (So how can you avoid my mistake?)

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

您可以采取幾種方法，我應該早點考慮：

1. Focus on a particular branch of data science such as natural language processing or data visualization.
   專注于數據科學的特定分支，例如自然語言處理或數據可視化。
2. Focus on a domain and sculpt your data science skills around projects in that domain.
   專注于某個領域，并圍繞該領域的項目雕刻您的數據科學技能。

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:

在獲得幫助以擺脫困境后，我采取了第二種方法。 利用我的教育背景，我專注于從老師的角度解決與教育領域有關的問題。 這導致我：

1. Influencing a hiring decision based on the academic needs of students.
   根據學生的學術需求影響招聘決定。
2. Created an overview of my school’s performance in a concise report.
   在簡明的報告中概述了我學校的表現。

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

   使用貝葉斯T檢驗確定我的復習課是否提高了學生的理解力以及提高了多少。

4. Analyzing state exam questions to guide curriculum decisions.
   分析州考試題以指導課程決策。

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.

這些項目我放在我的LinkedIn個人資料中。 他們引起了我意料之外的人們的注意。 引起了外部學校顧問的注意，他們最終提供了很多未來的幫助。 它吸引了一位Facebook招聘人員的注意，該招聘人員的相關數據科學/教育職位的起薪超過13萬美元。 討論我在這些項目中的經驗使我輕松通過了第一輪采訪。

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…

自從我變得更加專注之后，我獲得面試和進一步進步的速度很快就提高了。 同樣，鑒于我的情況，它不是最快的，但是與我以前的速度相比，這是一個巨大的進步。 每次采訪都改善了我的自我介紹。 直到最后……

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

我成功了！ 我找到了自己夢dream以求的角色，并闖入了數據科學領域！

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).

在撰寫本文時，距這個新職業生涯還不到三個月，這簡直令人難以置信！ 與我共事的人很棒，我得到不斷的反饋，我的工作具有立竿見影和/或未來的影響，我為此而受到贊譽(作為老師，您很少得到這樣的幫助，所以對我來說很重要……)而且我還是個內心的孩子)。

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.

如果您仍在尋找自己的職業，那就知道那并非不可能。 你能行的！ 請盡快專注于您要在該領域中要做的事情。 如果您仍在嘗試，那還可以。 但是我建議盡可能快地這樣做。 如果您是父母或與我有類似的情況，請知道這將花費更長的時間，但是您會到達那里。

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!

當您到達那里時，您將反思到那時的旅程。 您將回顧所有優點和缺點。 最終，您將轉向新職業的未來，并為入門做好準備！

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:

謝謝閱讀！ 如果您發現這篇文章很有幫助，但還沒有從我的旅程中找到一些技巧，則可以在下面閱讀有關它們的信息：

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，如果您以數學背景進入該領域，并且認為需要幫助組織學習計劃，請在下面的本文中查看我的建議：

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

您可以在這里關注我，也可以通過Linkedin和Twitter與我聯系。 在Twitter上打開DM。

Until next time,

直到下一次，

John DeJesus

約翰·德耶穌