Big Data Bytes: Data Scientists Wanted

“Businesses now looking for talent with deep analytical and statistical backgrounds include big publishers, portals, ad networks, and e-commerce sites – just about any company that possesses massive amounts of data. Salaries range from $75,000 to $100,000 for someone starting out with strong analytical skills and background to as much as $150,000 to $300,000 for experienced professionals.”–“Wanted: Data Scientist With a Human Touch”

“[Former Vertica CEO] Lynch told his staff during the February meeting that he has no intention of retiring. Indeed, he pledged to his staff that he would assist in starting-up or otherwise supporting no less than 20 Big Data start-ups in the Boston area over the next five years.”–“HP Lead Big Data Exec Chris Lynch Resigns”

“This is the time to be super aggressive.”–Chris Lynch

“As the amount of data in the world grows, the only certainty is that there will need to be more qualified peopled to make sense of it. That should be good news as we stop and salute our machine overlords.”–“The Age of Big Data”

 

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Domain Expertise vs. Machine Learning: The Debate Continues

By starting to rank all the data scientists participating in its competitions, Kaggle today advanced further its argument that data science is a generic set of skills that can be applied to any problem without prior domain expertise. Talking to The New York Times‘ Quentin Hardy, Jeremy Howard, Kaggle’s president and chief scientist, said that “it makes little difference for a top performer if the problem is public health or essays in Arabic. The argument that great data science is just about letting the data talk holds true.”

For a (short, recent) history of the debate, see Mike Driscoll’s summary of the deliberations of the panel arguing for and against machine learning and domain expertise at the recent Strata conference (video here), the results of a KDnuggets poll, and Mike Loukides’ passionate defense of expertise, concluding that “the real value of a subject matter expert: not just asking the right questions, but understanding the results and finding the story that the data wants to tell. Results are good, but we can’t forget that data is ultimately about insight, and insight is inextricably tied to the stories we build from the data.”

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Tom Davenport on Managing Data Scientists (Video)

[youtube https://www.youtube.com/watch?v=VK4-ASEUmgE?rel=0]

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Most In-Demand Data Science Skills

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Source: CrowdFlower, based on “3500 relevant job openings from LinkedIn.”

The folks at CrowdFlower excluded Excel from their list but noted that “that’s still something you see in myriad job listings. Old habits die hard.” Of course, data scientists don’t want to associate the “sexiest job of the 21st century” with old habits. Employers, however, want to cover all bases, sexy or not.

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Data Science Skills

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datascience_skills_proficiency

Source: Bob Hayes

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Survey: The Hunt for Unicorn Data Scientists Boosts the Salaries of Predictive Analytics Professionals

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Base Salaries for Individual Contributors

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Base Salaries for Managers

Unicorn Data Scientists (upgraded from “sexy data scientists”) are hard to find and are paid more than $200,000 per year. A new survey finds that the rising data science tide lifts the compensation of all other data analytics professionals, even if they don’t know how to code.

The Burtch Works Study: Salaries for Predictive Analytics Professionals is based on interviews with 1,757 data analytics professionals conducted over the 12 months ending April 2015 by executive recruiting firm Burtch Works. It is a unique source of information in that it does not rely on self-reporting or data provided by human resources departments. It also provides insights into how the demand for data scientists impact the salaries of other data analytics professionals because it excludes data scientists, covered in a separate Burtch Works study, published earlier this year (I wrote about that study here).

Burtch Works defines predictive analytics professionals as those who can “apply sophisticated quantitative skills to data describing transactions, interactions, or other behaviors of people to derive insights and prescribe actions.” Data scientists are a subset of this group—they have the “computer science skills necessary to acquire and clean or transform unstructured or continuously streaming data, regardless of its format, size, or source.”

The additional computer science skills put data scientists on top in terms of compensation regardless of their levels of experience and managerial responsibilities but predictive analytics professionals are keeping up, seeing their salaries and bonuses rise. For example, the median base salary for the most experienced individual contributors rose from $115,250 last year to $125,000 this year and for managers managing teams of ten or more the median base salary rose from $225,000 to $235,000.

Predictive analytics professionals continue to benefit from the increasing demand and short supply for their quantitative analysis skills. The median base salary of individual contributors varies from $76,000 for those at level 1 (0 to 3 years of experience) to $125,000 for those at level 3 (9+ years of experience). The median bonus received varies from $8,100 to $18,100, depending on job level.

The median base salary of managers varies from $125,500 for those at level 1 (1 to 3 reports) to $235,000 for those at level 3 (10+ reports). The median bonus received by managers varies from $23,000 to $75,000 depending on job level.

More and more people are attracted by the demand for data analytics professionals and the potential to become a unicorn. Data recently released by the National Center for Education Statistics, according to Phys.org, shows bachelor’s degrees in statistics grew 17% from 2013 to 2014. This marks 15 consecutive years the number of undergraduates in statistics has risen, increasing by more than 300% since the 1990s. In addition, from 2000 to 2014, master’s and doctorate degrees in statistics also grew significantly at 260% and 132%, respectively.

“The Bureau of Labor Statistics projects job growth for statisticians will increase 27% between 2012 and 2022, outpacing the projected 11% rate for all other occupations. The number of graduates in statistics each year—approximately 2,000 bachelor’s degrees, 3,000 master’s degrees and 575 doctorate degrees—seems unlikely to match this demand,” says Phys.org.

Originally published on Forbes.com

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The Data on Data Scientists (Infographic)

Data-Scientists-Infographic

Source: Bob Hayes

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The Data Science Interview: Edwin Chen, Twitter

I don’t do pure research—my analysis enables real-world functionality

Currently mining terabytes of tweets as a data scientist with Twitter, Edwin Chen studied math and linguistics at MIT and then crunched numbers at Peter Thiel’s hedge fund, Clarium Capital Management. He blogs on topics of interest to data scientists such as crowdsourcing text analysis with Amazon’s Mechanical Turk or ggplot2, a data visualization tool. The following is an edited transcript of our recent phone conversation.

When you went to MIT, what were your future plans?     Continue reading

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DataKind’s Jack Porway on Data Science

[youtube=http://www.youtube.com/watch?v=Mm1RplOU0cQ&w=560&h=315]

“If you leave an excited data scientist on his own to solve a problem, he’s going to solve his own problem – which is usually parking his car, or finding a bar to drink at. The trick that we worked on was actually less about data and more about translation, about finding a way for data scientists to speak the language of the people who were trying to solve the big problems… the biggest [challenge] is actually the framing of the problem: really finding the question. As any good data scientist will tell you, it’s not so much about the data, it’s the question you start with”–Jack Porway, DataKind

More here

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Where should you put your data scientists?

[slideshare id=61486991&doc=whereshouldyouputyourdatascientists-160429025555]

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