Data are becoming the new raw material of business
The Economist


Continuing Your Data Science Job Hunt Through the Holidays

xmas-wishThe holidays can seem like a tough time to job search, people are out of the office and holiday schedules are hectic.  But there are lots of things you can do to take advantage of this time, keep your search moving forward, and set yourself up for post holiday success. 

  1. Review your skill set

Read through every job description you can, even the ones for jobs that didn’t originally interest you. Where are your skills gaps? If you see fluency in C++ in one or two job descriptions, but not on most, you might be okay not knowing it well. But if you see fluency in C++ listed over and over, the next few weeks are a great time for you to work on learning it.

  1. Take on a new project

One of the best things you can do to really master those new skills (and demonstrate your knowledge) is to apply them. We’ve been publishing links to lots of publically available data sets on our blog. Take one and treat it as a case study, what problem might this company or organization have, and how can you use data science to solve it? You can add your work to your github, blog about it, or share it on your LinkedIn! These are publically available data sets, so definitely show off your work.

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Data Scientist Salaries

money-548948_960_720At The Data Incubator we’ve worked with hundreds of Fellows looking to enter industry and our alumni work at companies including LinkedIn, Palantir, Amazon, Capital One, and the NYTimes.  

Starting salary is one of the most common concerns for professionals entering any field, but as we’ve only been using the job title “Data Scientist” for about eight years it can be particularly challenging for prospective data scientists to find good information on their job market. LinkedIn and Facebook were the first to give employees on their data teams the title of data scientist, but now there are thousands of data scientists working across all industries alongside data engineers, data analysts, and quantitative analysts.

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5 secrets for writing the perfect data scientist resume

handshake-2056023_960_720Data scientists are in demand like never before, but nonetheless, getting a job as a data scientist requires a resume that shows off your skills. At The Data Incubator, we’ve received tens of thousands of resumes from applicants for our free Data Science Fellowship. While we work hard to read between the lines to find great candidates who happen to have lackluster CVs, many recruiters may not be as diligent. Based on our experience, here’s the advice we give to our Fellows about how to craft the perfect resume to get hired as a data scientist.

Be brief: A resume is a summary of your accomplishments. It is not the right place to put your little-league participation award. Remember, you are being judged on something a lot closer to theaverage of your listed accomplishments than their sum. Giving unnecessary information will only dilute your average. Keep your resume to no more than one page. Remember that a busy HR person will scan your resume for 10 seconds. Adding more content will only distract them from finding key information (as will that second page). That said, don’t play font games; keep text at 11-point font or above.  Continue reading

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