Are you showing employers results on your web page that a worse ML practitioner can't match.
Putting results from a kaggle competition on my LinkedIn page landed me my current job (and I am still contacted by potential employers every couple weeks).
The employers of the world aren't stupid, but they aren't omniscient either. So you need to make it easy for them to see that you have the skills you claim.
I don't know how sensitive the number of job contacts is to your ranking. My hunch is that a lower ranking would still establish credibility.
I'm convinced of it primarily because I'm convinced that the majority of activities that human workers perform do not require general intelligence (ie. strong AI). This includes most manual tasks : cleaning, cooking, customer service in restaurants, etc, but also many tasks performed by office or even "knowledge" workers.
A product my previous company developed replaced over 20K workers over a period of years. Few people even know it exists.
Once you are aware of this and follow the news you see it happening in virtually all domains: e-discovery systems replacing attorney hours, automated news story generation, etc. One area that has been lagging is robotics but this will start to develop very quickly, especially with the new DARPA Robotics Challenge.
Now to be clear many of the "Big Data" applications people are talking about may not fall into this human labor replacement category, but the underlying technologies are essentially the same.
It doesn't work like that. You LinkedIn profile might easily land you any job in Software development, but not consulting.
In my opinion, if you want to do consulting for big corp. you should figure out what it takes to it. An attractive website and presentation, few buzzwords, client testimonials, business cards, and the other blablabla. Yes, it's irrelevant (and shitty) to what you are actually doing, but that's actually the world of consulting.
Person who can do X - "I've been saying over here I can do X."
Big Corp - "Oh. We don't look over there, it's not how it's done."
I think I'm seeing part of the issue here.
EDIT ADDED: It seems like a really broken market if buyer decisions are completely orthogonal to the product being purchased.
I'm convinced that businesses could save trillions of
dollars by applying existing weak AI to their problems.
I have had a website and a LinkedIn profile for over a year that make
this fairly clear. How many consulting inquiries have I had ? Exactly
zero.
You're right that adoption is very slow. I'm convinced that businesses could save trillions of dollars by applying existing weak AI to their problems. Why aren't they doing it ? For one thing there's a huge gulf between the average business person's understanding of what is possible and what actually is. On the other hand the people who understand the technology don't have domain experience in various businesses. You can't develop solutions if you don't know what the problems are and it's very hard to guess at what economically relevant problems exist in fields you've never worked in.
There are probably other barriers as well. Domain experts are unlikely to champion technologies that may, well, replace them. Bayesian networks were developed in academia 20 years ago that outperformed doctors at medical diagnosis. Why aren't they being applied ? There are probably many reasons but I suspect conscious or unconscious resistance on the part of the medical community plays a significant role.
As for a talent shortage, I don't buy it. I'm exactly the sort of person this article talks about, with a strong mathematical background, excellent implementation skills and real world experience in developing and applying machine learning algorithms that have made millions of dollars for my former employers. I have had a website and a LinkedIn profile for over a year that make this fairly clear. How many consulting inquiries have I had ? Exactly zero.