How to Rock Your Data Science Career: 7 Career-Boosting Tips

Data science careers are growing faster than the national average at almost 20%!

With a median annual salary of $114,000 or more, a data science career is one of the most lucrative career paths for recent graduates.

But where do you start? What do you need? How do you move up in your field?

Find out with these seven actionable tips for building a fulfilling career in the data science Industry.

1. Get a Degree

Your career doesn’t start on the first day of the job. It starts with the decisions you make leading up to it.

If you want a leg up in this industry, the first thing you need to do is pursue an applicable degree.

And if you really want an advantage, consider these schools with top-rated data science programs:

  • University of Evansville in Indiana
  • University of Michigan Ann Arbor
  • Brigham Young University
  • Saint Mary’s University in San Antonio
  • Smith College
  • Arkansas Tech University

Some careers, like data statisticians and engineers, often require a master’s degree.

If you’re looking beyond a bachelor’s degree, consider Master’s programs at Columbia University, NYU, Northwestern University, or DePaul University in Chicago.

2. Get an Internship

It’s easy to get lost in academics. But don’t forget about gaining valuable “real world” experience in your industry. The best way to do this is to pursue a data science internship.

There are several ways to find both paid and unpaid internships.

First, look for leads at your college or university. Preferably, your data science department.

Many colleges have bulletin boards or online listings for jobs, tutoring, and internships. You can also talk to a professor or available college advisers for more leads.

Another way is to contact the company you eventually want to work for.

Have your eye on a dream data job at Amazon, Deloitte, Sumo logic, or even Google itself? Bookmark their career pages to stay updated on their latest internship opportunities.

You could also find an internship contact to email directly.

The internet is a treasure trove for internship leads as well. Job sites like Indeed, Monster, Simply Hired all list internships. You can also find internship ads on Craigslist, and more recently, Google jobs.

3. Discover Your Strengths

Courses and internships are instrumental for discovering the right career path in data.

But, a job is just a job, right? Wrong.

It’s critical to understand your strengths and weaknesses in order to find the most fulfilling and sustainable long-term career.

The best way to do this is to simply try lots of different things. Diversify your courses and job experiences. The learning stage is the perfect time to discover your natural skills and what you can improve.

To find out which valuable skills you’re lacking, check data science job ads to learn what employers are really looking for.

Job ads tell you everything you need to know. Some companies may require you to be proficient in a certain type of data software or computer language. Some may require more experience.

4. Keep a Data Science Career Portfolio

How do you stand out in a sea of job applicants? How do you prove your worth to a company that doesn’t even know you exist?

You need a track record. Specifically, you need a sleek portfolio that highlights your data science achievements.

For example, if you’re building a career in data visualization, make sure to save all your charts, graphs, scatter plots, and motion graphics.

A persuasive portfolio is the perfect companion to a resume that highlights your strengths, results, and academic achievements.

To stay connected to the data industry, consider making a LinkedIn profile. You can showcase your objective statement, career experience, accolades, endorsements from colleagues, and any data science publications you’ve contributed to.

5. Become a Contributor

If you haven’t written for any publications yet, now is a good time to start. Writing is a valuable skill you don’t want to lose. 

Data science publications and peer-reviewed journals are a great way to beef up your portfolio and career network.

Here are a few publications to contribute to:

  • The Code Data Science Journal
  • Data Elixir
  • Data Science Weekly
  • Bill O’Reilly data Newsletter
  • Analytics magazine

Consider starting your own blog to get your name out there too. 

Follow top data science blogs to inspire your own. More top bloggers to check out include Vincent Granville, Rich Brueckner, and Ryan Swanstrom.

6. Get Social

Now that you have blogging covered, let’s move on to social media. 

You can find tons of data science influencers on Twitter, like Merv Adrian, Carla Gentry, Judith Hurwitz, Marcus Borba, Cindy Houston, and Kirk Borne.

Why is this important?

Data science isn’t static. It’s a dynamic field that changes in tandem with technological innovation and society.

Following influencers is another way to discover the latest, most in-demand skills in your industry.

It’s important to stay in the loop, so you don’t fall behind. But also use this opportunity to grow your own social media following as well.

7. Become an Authority

Becoming a recognized social media authority in data science can do wonders for your career.

Here are a few more ways to become a trusted authority on data science:

  • Start a Twitter account
  • Apply for data science fellowships
  • Regularly submit your work to data science journals
  • Give a TED Talk
  • Participate in data science conventions

Contributing to major news networks, like the New York Times or CNN, as a data expert is another way to grow your data science career.

The more visible (and effective) you are on social media, the more journalists will take an interest.

Your Next Career Move

Don’t hesitate to take action on your career dreams.

You have a passion for data science, one of the fastest-growing industries in the world. The last thing you want is to get left behind.

Start realizing your potential by putting these tips into practice. And don’t forget to check back often for more tech news and tips to guide your data science career.