What Jobs are Hot?

I’m back at it again for at least one more post on that California salary data I put together. This time I want to look at our data with a bit more focus. I want to see which tech jobs have grown between 2013 and the present, with respect to the number of positions and salary. I’m starting with 2013, since some of the job titles are missing in the 2011 and 2012 data. We’ll use our usual filter to only focus on the thirteen non-managerial tech job titles, and we’ll look at the state as a whole.

WITH Year2013 AS
(
SELECT SOC_Code, Occupation, Year, Employment_Estimate FROM TotalData
WHERE [year] = '2013' AND
MSA_CODE= '000000'
AND SOC_Code LIKE '15-1%'
),
Year2016 AS
(
SELECT SOC_Code, Occupation, Year, Employment_Estimate FROM TotalData
WHERE [year] = '2016' AND
MSA_CODE= '000006'
AND SOC_Code LIKE '15-1%'
)
SELECT Year2013.Occupation, Year2013.Employment_Estimate AS Employment2013, 
Year2016.Employment_Estimate AS Employment2016,
(Year2016.Employment_Estimate - Year2013.Employment_Estimate) AS RawGrowth,
ROUND(
	(CONVERT(float,Year2016.Employment_Estimate) 
	     - CONVERT(float,Year2013.Employment_Estimate))
	/CONVERT(float,Year2013.Employment_Estimate)*100,2) AS PercentIncrease
FROM Year2013 INNER JOIN Year2016
ON Year2013.SOC_Code = Year2016.SOC_Code
ORDER BY ROUND((CONVERT(float,Year2016.Employment_Estimate) 
    - CONVERT(float,Year2013.Employment_Estimate))
	/CONVERT(float,Year2013.Employment_Estimate)*100,2) DESC

Since “other” isn’t a very helpful designation, Web Developer is the fastest growing tech occupation between 2013 and 2016. This is interesting, since it’s on the lower side of the salary scale (see my last post). This leads to another question: how did salaries change during this time period? To run this query, just take the one above and replace each instance of “Employment_Estimate” with “Mean_Annual_Wage”

Overall, there is a lot of very impressive growth for a three year period (though how much did California rents go up by in the last three years?…) It is clear that Application Development and Web Development have been the two “hottest” areas if you consider both job and salary growth.

Just for fun, let’s expand our query to all jobs in California. First, let’s see which jobs have increased in number the most in the last three years, and let’s only look at jobs with at least 1000 employed in it.

I’m surprised to see Graduate TA on this list. Hopefully it’s because they are giving more graduate students funding. I’m also somewhat surprised to see camera operators and video editors make the top 10. The growth in personal care aides is definitely a sign of our times and demographics. Let’s take a look at the bottom of this list…

Huh? So we need video editors and camer operators but not actors apparently. You know what’s next; let’s run the same query but with salaries. I set a minimum of 100 people in the occupation in 2016.

What a fascinating mix of old and new. Genetic counselor is the job of the future, but there are three railroad-related occupations in the top 10. It looks like there aren’t enough people to fill those old school railroad jobs, so salaries went up. And the jobs with the largest decrease in wages…

This is very interesting as well. Graduate TA’s are both one of the fastest growing occupations but have a severely decreasing salary at the same time. The average salary in 2013 (~$44k) does seem surprisingly high, though it would make sense if you consider that TAships are often halftime, and they are calculating the salary on a fulltime basis. It also looks like the funeral industry is facing decreased wages.

I’ve enjoyed looking at this data set. It offers a really interesting glimpse into the California tech labor market. Next time, however, I’ll write about something else.