Obviously the answer depends on the skill level, but based on the few machine learning contractors I've worked with on oDesk, I would guess about $30-$40/hour is average. However, I wanted to check with some real data. I have access to our full database, but a more useful answer would allow people to see how to do this for other skills by simply scraping our search results (we have an API, but I don't know how to use it yet and I wanted to try the BeautifulSoup package).
First step was to reverse-engineer our search syntax and the HTML for profile rates. A contractor search of "machine learning" gives this:
"https://www.odesk.com/contractors?nbs=1#q=machine+learning"
and if I click on the next 10 results, the url is:
"https://www.odesk.com/contractors?nbs=1#q=machine+learning&skip=10"
I then checked to see what happens if I set "skip=0"---it returns that same thing as the first search URL, so now know that I can just write one function that returns the query URL, with parameters of "q" and "skip."
Next, I needed to find out how the rates are stored. Using Chrome's awesome "Inspect element" feature, I found that the rates for the 10 returned results as listed as "rate_1", "rate_2", and so on:
The rest was pretty easy---I just wrote two loops to collect up wages. I saw that we had some clear false positives, which I filtered out. This actually brings up a big problem on oDesk that we've been working on---namely that until recently, we had no standardization of skills, which made it hard to match people or do really good, highly specific queries. We've now moved to a closed (but expandable) vocabulary of skills, ala StackOverflow which in the long run will make it much easier to do matching and recommendations (and little data projects like this). That's a topic for another blog post. So, returning to the original question, my answer based on a pretty tiny sample:
Min: 16.67
Max: 100.0
Mean: 39.6983333333
And here's my pretty crappy but for-the-moment-functional code on GitHub:
