BUILDING A CAREER IN DATA SCIENCE

BUILDING A CAREER IN DATA SCIENCE
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Welcome to episode #177 of the Super Data Science Podcast. Here we go!

In the incoming years, we will be witnessing a radical change in data science education. Would you agree?

On today’s episode of Super Data Science Podcast, Zach and I talk about utilizing online platforms, integrating machine learning in the healthcare industry, and sighting the future of the formal education.

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ABOUT ZACHARY LOERTSCHER

Zachary Loertscher is currently finishing his bachelor’s degree in Business Analytics from Brigham Young University – Idaho. On his free time, he self-learned various tools such as Tableau, Python, R, SQL, and Business Objects Data Services. He curated the List of Epic Data Science Mentors for enthusiasts who want to dive in Data Science.

This type of out-of-the-box thinking is exactly what you need to stand out in a career in data science. For more tips & tricks on how to move forward, don’t miss our career-focused data science event: DataScienceGO 2018.

OVERVIEW

Getting the degree from a university and highlighting it on your resume could get you the ultimate dream job. Well, that’s what we are perceived to do by society.

In this digital age, it’s just fitting to question the steadiness of the traditional system of our education and look into the incorporation of online courses in your learning journey. This is not to say that studying on a fixed schedule inside a four-cornered classroom and finally getting that diploma is becoming invaluable. With the fast-paced learning environment, we should keep up. Academies should have up-to-the-minute curriculums for students and we should make use of the ever-available resources in front of us.

For example, Zach is just finishing his undergrad but he went the extra mile of studying various tools by exploring online courses. His eagerness to learn data science also led him to make the List of Epic Data Science Mentors. This list became popular and helped a lot of enthusiasts also. Aside from online courses, he utilized LinkedIn. He put his self out there – building a brand, posting a lot of content, and engaging with the data science community.

He’s also looking into using data science machine learning to help with healthcare issues. He’s spotted the opportunity where he can contribute more. He continues to learn by reaching out to people who work in the industry.

Zach and I share our thoughts on the current state of data science education for the most part of this episode. I believe that the most important thing is to be crystal clear on your intentions when getting a degree. It doesn’t matter if it’s online or traditional. Those online certificates are gonna be valued less and those university certificates are gonna be equally valued less. Having a degree indicates the possibility of contributing but there’s so many resources online that you can demonstrate it much more effectively and succinctly.

Remember: drive, motivation, discipline, and structure are required. Make your rules and follow your rules. Have a vision where you’re going. If you think you’re still lost, you might get inspired by when we talk about the most and least favorite parts of data science.

IN THIS EPISODE YOU WILL LEARN:

  • Zach is pursuing Business Analytics and learning more about the world of data science and machine learning. (05:45)
  • LinkedIn is a powerful networking tool to build your portfolio, engage with the community, and learn more about data science. (08:38)
  • Zach is looking at the opportunity to use and harness the power of machine learning to help with healthcare issues. (16:57)
  • Formal education vs. Online Courses. (23:22)
  • “It’s about making your rules and playing by the rules” – Kirill (31:30)
  • Drive, Discipline, and structure are very important if you want to do self-learning. (34:58)
  • “Data Science is the best field for entrepreneur lands.” – Zach. (41:56)
  • What’s their favorite part of data science?
    • Zach – Data Visualization. People can easily gain insights from well-presented data. (49:18)
    • Kirill – Breaking down the complex into simple. (51:43)
  • What’s their least favorite about data science?
    • Zach – Programming. (53:30)
    • Kirill – getting lost in the specifics of certain algorithms. (54:30)
  • Zachary prioritizes work-life balance. (56:40)

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