Data scientists making $300,000 a year | Wall Street Journal.

Without having anyone working (reporting to) them, according to the Wall Street Journal.

My opinion:

  1. Highly paid data scientists having nobody reporting to them? Indeed they have robots (computer programs working in batch mode day and night - harvesting, summarizing, reporting and analyzing data) working for them, to help them do their jobs 10 times faster. These robots do the job of a dozen data analysts (human beings).
  2. Some data scientists make fare more than $300K/year, but they usually are not on a payroll, and typically don't have a boss.
  3. Data scientists on Wall Street (who design high frequency trading algorithms, they are called Quants) easily make $500,000 a year, but the good money vanishes as soon as the algorithms stop working. 

Anyway, here's the WSJ story:

Tom Davenport, who is teaching an executive program in Big Data and analytics at Harvard University, said some data scientists are earning annual salaries as high as $300,000, which is “pretty good for somebody that doesn't have anyone else working for them.” Davenport also said such workers are motivated by the problems and opportunities data provides.

Read full story at http://blogs.wsj.com/cio/2012/11/28/how-cios-draw-big-data-talent/

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Comment by Vincent Granville on December 2, 2012 at 7:37pm

This type of salary is not the norm. I once talked to a Deloitte recruiter who said the compensation package for a Partner position was well above $300k, with practically no limit. A pharmaceutical company in Chicago (one of our clients) hired a Bay Area data scientist thanks to us, and the compensation was far above $200k. VP of analytics in the Bay Area can command $200K easily. As for me, my salary range for Chief Scientist (located in Seattle where there is no income tax, but working in California and Texas) has always been around $155k - $175k per year (not including bonuses), but with substantial revenue boosts when my patents were purchased. Plus, because of smart profits in the real estate in 2005 and gains in the stock market between 1998 and 2000 (not followed by losses!) and other smart financial choices, I don't need a high salary. I could survive in Seattle on $65k/year, although of course, that's not my plan. But it gives me a competitive advantage over candidates who really need tons of money. 

Anyway, I left the corporate world to create my start-up with two partners, but I'm still - more than ever - a data scientist, and my revenue has nicely increased since I left, although I am not on any payroll anymore, and I am not a consultant either (except occasionally).

Comment by HURT on December 2, 2012 at 1:56pm

However, such professionals have been employed for a long time in financial companies. In France for example, there are very known courses in financial mathematics, of which graduates scatter in the world large banks, in particular in London. But the finance companies tend to reduce their staff because of the regulation.

Comment by Vincent Granville on November 30, 2012 at 7:43am

Data scientist stars are in high demand and highly paid. If you are not a star, forget about it - you'll never get an interview (except if you just graduated from a good University). But what makes you a star, and what makes a good University program? Interesting questions.

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