Tag Archives: data science

Data scientists’ pay: details worth $10K

The median data analyst makes about $98,000 –including bonuses — in the U.S., according to a new salary survey from O’Reilly Media. But data people being what they are, the report includes a regression that allows anyone to compare their salary based on 27 variables from location to experience, from tools used to gender.

The survey of 816 people (about two-thirds from the U.S.) isn’t random, and the fact that it deals with data wranglers certainly caught our eye. But a survey that actually breaks down the differences among salaries really stands out.

Why aren’t more salary surveys done this way?

totalsalaries_oreilly

Salaries have been a tricky thing in the past few years, especially for journalists. Publishing salaries of state or university workers is common at news organizations. They get lots of viewers — and a lot of push back for privacy invasion.

But others have argued that knowing everyone’s salary is the only way to insure pay equity,  and that salary is based on merit not one’s ability to negotiate. It can also avoid scandals such as an $800,000 city manager in a low-income suburb of Los Angeles.

Yet even if the human resources department decided everyone’s pay should be transparent, that still doesn’t provide context — is there a good reason someone earns more?

Which is why the O’Reilly survey is important. Even with the 27 variables that contribute to salary, the regression only explains about 58 percent of the variance. Still, even the attempt to explain variance reveals some interesting findings:

  • Geography matters. Not surprisingly, data scientists in California and the Northeast make more (between $17K and $26K). But working in Texas had the second-highest boost.
  • Startups don’t pay well; neither does government. Analysts in education lowered the expected salary by $30K; start ups drop the salary about $17K.
  •  Experience counts. Every year of age and each year working with data, together adds about $2,500 to the expected salary. Using tools such as Python, Natural Language Processing, NumPy and R can *each* add $1,900 in expected salary. SQL, Python, Excel and R are the most common tools used.
  • Being female hurts. The survey shows a $13K gender pay gap among data scientists — and says no differences in tools, experience or other factors account for it. See also Wage Debate at the Oscars.

Data science –whether it’s in journalism, government contracting or elsewhere  — is a rapidly expanding field, which makes predicting salaries difficult. The O’Reilly survey may not be perfect, but it gives people real tools  to create  transparency, without invading privacy.

–Jodi Upton

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Our new geek-in-chief

My data science friends were all a-buzz recently: America now has a Chief Data Scientist.

DJ Patil, a former LinkedIn chief scientist and a chaos theorist, was appointed by President Obama as top cheerleader and data policy officer for Big Data.

“One of the most awesome things for me personally,” said Patil in his post-announcement address to the STRATA conference “is how much our government has embraced data science.”

As evidence, Patil points to the dashboards the President uses, the 135,000 data sets released on data.gov., and how it all contributes to government transparency and solving our social ills.

It is indeed an exciting time. But as the new national spokesman for government data, Dr. Patil has a lot of explaining to do.

The Veterans Administration – the agency awash in charges that dozens of hospital leaders falsified wait-time data to get bonuses while veterans died – recently responded to a USA TODAY open records’ request by sending data as a jpeg, a photo format.

The government didn’t release the data. It released a picture of the data.

That doesn’t even touch the politics that prevent collecting the right data in the first place.

For 19 years, the National Rifle Association has blocked federally-funded gun research. As a result we have almost no national data with details on who is injured or killed by guns, under what circumstances, what caliber, where the gun came from, whether it was illegal, and what works to prevent gun accidents and trafficking.

When an unarmed black teenager in Ferguson, Mo was killed by a police officer, everyone wanted to know: ‘How many people have been shot by cops– black or any race?’

Good luck finding out. In spite of decades of debate, the data is not collected.

So welcome aboard, Dr. Patil. We need a chief geek. But your biggest challenge may be bureaucracy below your new boss.

–Jodi Upton