This exercise was done to understand the software skills that are in high demand for Data Science. Analysis was done by extracting the job postings from popular online websites. The findings are interesting. R continues to be the most popular skill, found in 70% of the postings. Python follows as a close second. Surprisingly, in spite all the talk about "Big Data Science", SQL comes up third. This shows that traditional RDBMS still continue to be the base for machine learning work today.

Details of the analysis can be found here : Analysis of Data Science Job postings. Below are some highlights. The following chart gives the relative importance of skills. A frequency of 0.5 means the skill is found in 50% of the postings.

As seen, R, python and sql are the top 3 skills found. Java continues to be a favorite programming language. Interestingly, SQL triumphs hadoop in the skill list. 

Association rules mining was done to find which skills occur together. The following are the results of ARM (rules) on this skill set

 lhs             rhs            support confidence      lift
1   {}           => {sas}        0.3469388  0.3469388 1.0000000
2   {}           => {java}       0.4081633  0.4081633 1.0000000
3   {}           => {hadoop}     0.4693878  0.4693878 1.0000000
4   {}           => {sql}        0.5714286  0.5714286 1.0000000
5   {}           => {python}     0.6326531  0.6326531 1.0000000
6   {}           => {R}          0.7142857  0.7142857 1.0000000
7   {tableau}    => {R}          0.1020408  1.0000000 1.4000000
8   {javascript} => {java}       0.1224490  1.0000000 2.4500000
9   {java}       => {javascript} 0.1224490  0.3000000 2.4500000
10  {javascript} => {sql}        0.1020408  0.8333333 1.4583333
11  {javascript} => {python}     0.1020408  0.8333333 1.3172043
12  {big data}   => {hadoop}     0.1020408  0.7142857 1.5217391
13  {spark}      => {hive}       0.1224490  0.8571429 3.2307692
14  {hive}       => {spark}      0.1224490  0.4615385 3.2307692
15  {spark}      => {hadoop}     0.1224490  0.8571429 1.8260870
16  {spark}      => {R}          0.1020408  0.7142857 1.0000000
17  {perl}       => {sql}        0.1224490  1.0000000 1.7500000
18  {perl}       => {python}     0.1224490  1.0000000 1.5806452
19  {perl}       => {R}          0.1020408  0.8333333 1.1666667
20  {mapreduce}  => {hive}       0.1020408  0.5555556 2.0940171
21  {hive}       => {mapreduce}  0.1020408  0.3846154 2.0940171
22  {mapreduce}  => {hadoop}     0.1632653  0.8888889 1.8937198
23  {hadoop}     => {mapreduce}  0.1632653  0.3478261 1.8937198
24  {mapreduce}  => {R}          0.1224490  0.6666667 0.9333333
25  {ruby}       => {java}       0.1020408  0.6250000 1.5312500
26  {ruby}       => {sql}        0.1632653  1.0000000 1.7500000
27  {ruby}       => {python}     0.1428571  0.8750000 1.3830645
28  {ruby}       => {R}          0.1020408  0.6250000 0.8750000
29  {pig}        => {hive}       0.1428571  0.7777778 2.9316239
30  {hive}       => {pig}        0.1428571  0.5384615 2.9316239

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