Database Reference
In-Depth Information
Initially I came to PlaceIQ more for the challenge of working with all of the
location data, movement data, and ad requests than to specifically work in ad
tech. But now that I've been exposed to more of the ad tech industry, I find it
much more interesting than I thought it was going to be.
Gutierrez:
In theoretical terms, how do you describe the work you do to
other data scientists or to people who work in quantitative fields?
Lenaghan:
In a word, I'd tell them that what we do is
ingest, transformation,
and contextualization
. We ingest enormous amounts of location data—on
the order of 50 billion records a month. Then we essentially do large joins
against our geospatial layer. We run many different types of classifiers on the
geospatial layer to determine whether or not a particular tile is residential or
retail or mixed-use. Then we apply a domain-specific language we've devel-
oped to build these audiences into profiles that not only contextualize the
places but also add more insight into the patterns we see in the aggregate
movement data.
Gutierrez:
How would you explain what you do in more qualitative terms
to a five-year-old?
Lenaghan:
Five-year-olds are increasingly sophisticated about mobile devices
these days. I'd say to a five-year-old that we are mappers of the world. We're
using the signals that come out of people's phone to better understand the
types of people in any given place in the world.
Gutierrez:
That's an explanation I could tell my mom: “Jonathan is using
the phone signals to map the flow of different types of people in our world.”
“Okay, that makes sense, Sebastian.”
When you did you realize that you wanted to work with data as a career?
Lenaghan:
When I was an undergraduate, I majored in physics. I knew that I
wanted to become a physicist—more precisely, a professor of physics. I really
looked up to all of the professors I had as an undergraduate, and I was very
excited about graduate school. You might suppose from my future career
trajectory that I must have been immersed in experimental data when I was
working in physics, but I was actually working more on the formal theoretical
side of particle physics.
My study was the formal side of the strong interactions described by the
theory of quantum chromodynamics: how quarks and gluons interact with
each other and form neutrons and protons and things like that. Even if we
can't solve the governing equation from quantum chromodynamics, we can
still run simulations on it and we can solve it within certain limits.
At the time, I didn't really care what any of the experiments relating to the
strong interactions were telling us. I was just interested in answering the ques-
tion, “What can I learn from this defining equation using all the constraints of
