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If you’re looking for a job in the big data world, chances are you may be overwhelmed. The fact is that there are more jobs out there than there are applicants.  A good problem to have, to be sure, but how do you decide which jobs to go after in such a wide playing field?

Having too many choices can be just as debilitating as having too few, so apply these tips to your job search to find the perfect match for your skills, talents, and interests.

  • Don’t get hung up on titles. One company’s “data analyst” may be another company’s “data scientist” or “data visualiser.” There is no standard definition for any job titles in the big data world, so don’t limit yourself to searching for a single title or only applying for jobs that explicitly use the title you’ve had in the past or thought you wanted for the future. Read job descriptions closely instead.
  • Focus on your unique skills set. If your goal is to be one of these so-called big data “unicorns,” then you need to emphasise your unique skills set. What makes you the only person for the job? Things like programming skills and maths degrees may be important, but your experience and insights may be the winning combination, so make sure you are calling them out on your resume, cover letter, and in your interview.
  • Look in other sectors. Big data is growing fast in a host of different sectors. Up until now, you might have been focusing on the retail, manufacturing, and information sectors, but research shows that industries like finance, education, hospitality, and healthcare are growing. Don’t fence yourself into a particular sector, and definitely branch out if you have experience in a particular, albeit smaller, industry.
  • Show off your visualisation skills. You don’t need to be a graphic designer, but one of the traits a good data scientist must have is effective visualisation skills. Be sure your resume shows that off.  Display information in a clean, easy-to-read format. If you can be innovative in showing off your best qualities, do so. Stand out from the pack.
  • Don’t hide your unusual education background — accentuate it. Recruiters are finding more and more that applicants from diverse backgrounds including philosophy, liberal arts, statistics, and others. Don’t try to hide an unusual degree; instead, emphasise how it will help you in your new position.
  • Try the briefcase technique. Go into an interview with an example of how you can benefit the company. Ramit Sethi of “I Will Teach You To Be Rich,” calls this the briefcase technique, where you go into an interview armed with a short proposal for how you could solve a company’s problems. Be proactive and impress the interviewers with a demonstration of your expertise.
  • If you’re new, focus on full-time positions. If you’re new to the field, look for full-time, long-term positions instead of contract work. Companies looking to hire full-time employees are more often willing to invest in training, and you can pick up and improve your skills on the job.
  • Get involved. Hadoop is an open source platform, which means there is a thriving community out there using and improving it. Get involved, network, and participate in hobby projects on the side. This will not only improve and demonstrate your skills, but also help you make important connections.
  • Define the job you want before you start looking. This is good advice for any jobseeker, but you should be clear on the type of job you want before you even apply. A job with an established company will be very different from a job with a startup, even if they have the same title and description. Define what you want to help you narrow down your search as you go after it.

Once you’ve found the perfect job to apply for, let your talents speak for themselves. Avoid too much jargon, and definitely avoid acting as though you have all the answers. The best data scientists are curious, and have more questions than answers at any given time.

What other suggestions would you give someone looking for a big data job? I’d be interested in hearing your thoughts in the comments below, especially if you’re a recruiter or employer with experience hiring in the big data field.

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