10 steps to launch your carrier in data science
If you want to be a data scientist, several tips can help you get a job, be a freelancer, or start your own company.
Today, I reveal 10 of them based on several resources that will help you in your tech carrier.
Let’s start!
1. Data science is a lifelong learning carrier. Study!
In 2014, I got my degree as a computer scientist, and in 7 years, I have seen the IT area changing so much!
The term ‘data science’ is relatively recent! Thus, even with a bachelor’s degree in the area, it is always required to keep up-to-date.
To do so, never stop studying. If you are in a carrier transition, focus on one of the three cores of the area: business, programming, and statistics. Also, stay tuned in IT podcasts, youtube channels, recent scientific papers, and blogs.
Bonus tip: subscribe to IT podcasts, channels, blogs, and google scholar. Trust me, it is easier when the information comes to your email or your favorite video/podcast app!
Bonus tip 2: my favorite sources of information
- Analytics Vidhya
- Medium Toward Data Science
- Luke Barousse channel
- Tina Huang channel
- Mit technology review — pt-br or english
- Data Hackers Podcast — pt-br
- Pizza de dados podcast — pt-br
Also, the books from O’reilly are great to practice and learn. If you are starting, I highly recommend you to read Data Science for business
2. Create a portfolio
Experience comes with practice! We know that several positions are not filled because companies require years of experience!!! No worries, if you are in IT, you can create your own experience building a portfolio.
One of the area’s advantages is that you don’t need a house to practice your engineering skills, for instance. Plan a schedule to develop several side projects from your home and post them online.
It will help you study by demand and improve your technical skills.
- Run from basic/classical project
Data science is a multidisciplinary area with lots of applications.
However, there are several datasets that because famous over the years. Yes, you can create projects based on them, but not only. Pay attention if you are only using these datasets:
You can focus on the type of data you want to work with (medical data, images, finance) or expand among several applications and techniques — all according to your professional profile strengths.
3. Write a blog
I recently read an interesting post showing the importance of writing a blog. I’ve been writing for a few months, and I can personally relate to the benefits.
First, if you are a blog consumer, you know much that tutorials and posts help you understand many tasks. Furthermore, after you learn a subject, writing a blog post enables you to keep this knowledge to yourself (and others).
If it is not enough to convince you, it will expose you to the data science world and help recruiters see you.
4. Show your work
Social networks are here; use them!
If you wrote a paper, post it on your Instagram, Facebook, LinkedIn, etc.
If you finished a new project, use your social network to shout out!
If you found an excellent post (such as this one!), post it!
You may not create any content, but share what you read, listen to, and watch.
5. Be part of a community.
If you want to grow, be among those who share the same interests as you.
Of course, we are complex humans with many desires! However, in the professional field, being in a community helps you improve yourself, ask for help, and exchange.
Connect to others online and offline!
6. Pay attention to trends.
Trends are a key to what technology will develop. Pay attention to the news. I can also give you ideas on new projects.
7. Pay attention to your behavior
Are you tired? Probably everybody is!
Are you mad with chatbots that do not work correctly? Probably everybody is!
Do you miss anything in your daily life? It could become your next big project.
8. Talk about it
It overcomes the internet! Talk about data science to your family, friends, and anyone that stops to say hi!
People will you see as an IT professional, and every time you talk about it, it will positively affect you. It will strengthen your love for data analysis and its applications.
10. Be curious!
Data science is about solving problems. Be curious and exercise your creativity in every aspect of your life!
Any other tips? Comment!
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