This happens to be one of those rare instances where the benefit of hindsight does not make me regret something said flippantly on a panel. I deeply believe that in order to truly change the world we cannot simply "throw analytics at the problem." To that end, the medical and health industries are perhaps the most primed to be disrupted by data and analytics. To be successful, however, a deep respect for both the methodological and clinical contexts of the data are required.

It is incredibly exciting to be at an organization that is both working within the current framework of health care and data to create new insight for people, but also pushing the envelope with respect to individuals' relationships with their own health. The challenges are technical, sociological, and political; but the potential for innovation that exists in this space comes along very rarely.

I feel lucky to have an opportunity to move into the health data space now.

Sensor data

The past decade of development in "big data" has -- in large part -- been built on top of the need to understand web logs files. Somewhere between Web 1.0 and Web 2.0 people began to realize that there was a tremendous amount of underutilized value in these logs files. This spawned an entire big data ecosystem, and a whole new set of hardware and software tools to support it. Arguably, data science as a discipline and profession was also an offspring of this movement.

We have built technology and algorithms to understand the Web, and we have done a great job. Innovation in this space, however, is now focused on further abstracting away the technical detail in order to deliver analysis further up the business ladder. That is to say, we have by and large solved the web logs files big data problem, and are now trying to make it easier for everyone to participate. But, we have only just begun to even conceive of the scope for the sensor network big data problem.

I believe the next decade of exciting work for data scientists and engineers will be in creating an ecosystem around sensor data. By liberating the in-bound bytes from the Web, we have at once an entire new class of questions that can be asked, and a new class of hardware and software problems that must be solved.

This is particularly relevant to those considering starting a career, or making a pivot, into the data industry.

Strength of team

In my time at IA Ventures I have learned an enormous amount about the dynamics of technology startups, and what can contribute to their success. While this will not surprise those with startup experience, it bears repeating that the strength of startup's team is at least as important as the strength of its technology.

At Project Florida, the team that has been pulled together -- and continues to be assembled -- is one of the strongest I have ever seen. For those considering other opportunities, I would strongly recommend considering the people you will be working with just as much as problem you will be working on.

Of course, I would be remiss to conclude without giving a plug to make the Project Florida team even stronger. I will be looking to add folks to the data team immediately, and we are looking to grow the whole organization. If interested, please feel free to reach out to me directly about opportunities on the data team, or ping WeAre@projectfla.com for information about opportunities throughout the organization.

Here's to the next adventure!