How to Grow Your Career: A look at Data Analysts & Data Scientists

by Modis on March 3, 2014

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It’s been said that data science is the ‘sexiest job of the 21st Century.’ If anything, this claim is an understatement.

The facts behind Data Analysts

Data science is the job to pursue right now. Why?

  • Professional opportunities span multiple fields — from accounting to healthcare and high tech. No matter your passions or interest, there’s an opportunity to make a meaningful impact through data.
  • Data scientists are high in demand — according to one estimate, job postings increased by 15,000% between 2011 and 2012.
  • Between 2010 and 2020, the data scientist career path is projected to increase by 18.7 percent, beat only by video game designers. The big data industry is expected to be a 53.4 billion industry by 2016.
  • There’s a global talent shortage, which means that data scientists are in high demand but short supply. As a result, average salaries are trending higher and higher — the average data science salary in the U.S., according to Glassdoor, is $117,500. Not surprisingly, those with PhDs and experience can earn salaries as high as $650,000, based on a Reuters peHUB article.

If you’re reading this post, you’re probably wondering how to make this key transition in your career — maybe you’re entering the field for the first time or looking to grow from analyst to scientist.

The fact is, you don’t necessarily need a PhD or advanced education (though these qualifications can help). You can hack your education and make the jump from number “cruncher” to “mastermind” by honing the following skills: 

1. The basics

The first step to launching a data career is to develop skills to become a data analyst. As a data analyst, you need a basic understanding of statistics, best practices for handling data, and experience with basic software. Here is what you need to know:

-Basic SQL: How to create a MySQL server; an understanding of relational databases and Dimensional modeling; a thorough understanding of Excel, including VBA and Macros-Basic languages like HTML, JAVA, and XML; presentation skills to create reports, dashboards, and tables; math, statistics, and problem solving skills

W3Schools is a free resource that can help you learn basic technology skills. Pragmatic Works can help you build upon these basic concepts to start developing specialities and advanced knowledge to help you start the transition to becoming a data scientist.

2. Storytelling

Data science means more than crunching numbers. In addition to analyzing data, you need to be able to communicate key trends and important findings. Consider looking for courses in visual storytelling, presentation design, or blogging to make sure that your numbers deliver a stronger impact.

3. Statistical Software Packages

You need more than basic Excel skills to work with massive datasets. If you’re crunching numbers, it’s absolutely crucial that you learn a statistical program like SaS, R, Stata — in addition to at least one programming language like Ruby on Rails or Python. These skills will help you analyze numbers efficiently and creatively.

4. Distributed Computing Skills

As your datasets grow, your computer’s processing power shrinks. As a result, it’s important to learn skills that support distributed computing, so that you don’t lose momentum in your analytic capabilities. Look for certification programs that teach you how to use technologies like Hadoop and MapReduce.

5. Business Skills

Data is a double edged sword. When you have access to infinite information, you risk information overload. The best data scientists are able to think like CEOs, making tradeoffs to focus on key business initiatives. Practice the art of razor-sharp problem solving, creating solutions that are both actionable and optimized for growth.

5. Familiarity with Open Source Technologies

Some of the best solutions are peer-driven. Open source communities present a powerful opportunity for data scientists to (1) network with other professionals, (2) practice their skills, (3) find solutions at low costs, and (4) define the future of their professions. The value of open source is in the numbers — according to TechRepublic, data scientists who specialize in open source technologies earn more than professionals who work with proprietary software.

Final Thoughts

The best data scientists can effectively deploy left-brained and right-brained insight. They are quick on their feet, highly creative, and self-aware of the fact that there is no possible way to know everything about technology.

If you need a bit of structure — beyond what’s mentioned in this post — check out this new data science certification program from Cloudera, which will help equip you with a concrete set of skills. Not to mention, the founders are considered to be two of the world’s top data scientists.

The best data scientists are hungry for knowledge and continuously seeking new ways to learn — to them, glass ceilings are obsolete.

Ready to dive into the world of data analytics?

With data demand comes data jobs. At Modis, we are constantly adding data-based jobs to our listings, so your new career is just a few clicks away. Connect with your local Modis Recruiter to discover jobs in your area or apply for one of our current job listings here.

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