How To Make $100,000 A Year Crunching Data

Bernard Marr

Best-Selling Author, Keynote Speaker and Leading Business and Data Expert

Data scientists are sometimes called “unicorns” because of the unlikely confluence of skills employers need them to have. And so, they pay accordingly when they come across these mythical beasts — a good data scientist can expect to make at least $100,000 a year.

So, how do you get a job like that?

If you’re just starting out in the field, you will likely need to start as a data analyst and work your way up to becoming a data scientist — because there is no such thing as an entry-level data scientist. Data scientists are, practically by definition,experienced professionals with a variety of skills.

This excellent infographic outlines a roadmap of sorts towards becoming a well rounded data scientist, and touches on the fact that you must have an understanding of statistics, machine learning, text mining / NLP, visualization techniques, big data tools, data munging and ingestion, and more.

To this list I would also add an understanding of business, and especially the field in which you hope to work, because the best data scientists combine an understanding of the business with an understanding of the data to create real insights.

Assuming you already have (or are on the path to getting) these skills, there are some other important decisions you can make to ensure you land one of these high-paid dream data jobs that are out there:
Get a job with a startup.
True, a job with a startup might not offer the best long-term job security (they’re notoriously susceptible to boom and bust cycles) but they also tend to pay the most, on average. According to an O’Reilly survey from 2013, data scientists make an average of $130k a year with startups compared to $110k at public companies and $80k with government agencies.
Increase the number of tools in your toolbox.
Data scientists who use six tools or more get paid an average of $125k, while those who don’t average around $88k. Surveys also show that data scientists who can use the Hadoop cluster get paid considerably more. Upgrade your skills set, and you could seriously upgrade your earning potential.
Get your PhD.
OK, maybe not, but many of the top-paid data scientists in the field are coming from academics. Scott Clark has a PhD in applied mathematics which he originally used to create genome-mapping algorithms that he now uses at his data science job at Yelp. He told the Wall Street Journal, "Academia is slow and only a few people see your work. At Yelp, I can be pushing out experiments that affect hundreds of millions of people. When I make a small change to the Yelp website, I have a bigger impact." If you have any academic research in your past, be sure to put it on your resume or mention it in interviews.
Add “data scientists” to your keywords on LinkedIn.
Seriously, this one tip could get you found by hundreds of potential employers. A quick search on LinkedIn shows almost 64,000 job openings listed with the words “data science” in them, so recruiters are looking to fill jobs with a scarcity of workers.
Be willing to relocate.
Unless you’re already in one of the top 10 cities for big data jobs, that is. The data job market in Silicon Valley is big, of course, but there is big growth happening in cities from Raleigh, NC to Boston and Portland, OR to Denver, CO. If you’re looking for a high-paying job, look outside of California (where everyone else is looking, too).

This is an incredible time of exponential growth in the industry, so if you can parlay your skills from any number of fields — statistics, biostatistics, particle physics, computer science, economics, mathematics, and even social and behavioral sciences — into an entry level job as a data analyst, you can be poised for incredible potential as you gain experience and skills.

Are you in the data science field? What advice would you give to people trying to break in and become one of the mythological unicorns? Let us know in the comments below.

Thank you very much for reading my posts. Here at LinkedIn and at Forbes I regularly write about management, technology and the mega-trend that is Big Data. If you would like to read my regular posts then please click 'Follow' and feel free to also connect via Twitter, Facebook and The Advanced Performance Institute.

You might also be interested in my new big data case study collection, which you can download for free from here: Big Data Case Study Collection: 7 Amazing Companies That Really Get Big Data.

Here are some other posts from my Data Informed column:
The Hype May Be Over, bug Big Data Isn't
4 Things Big Data Can Do, and 3 Things It Can't Do
The Difference Between Big Data and a Lot of Data
The 5 Scariest Ways Big Data Is Used Today

About : Bernard Marr is a globally recognized expert in big data, analytics and enterprise performance. He helps companies improve decision-making and performance using data. His latest book is Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance'.

You can read a free sample chapter here.
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