Doing data science since before it was cool

Did you come here looking for Mark St. John-the-ecologist? Well, that's me, too (which also answers the question "Why are there so many bugs on your website?")

My journey into data science began with training in ecology, an intense field of applied statistics  (H. B. Sc., Biology, 1994, Carleton University, M. Sc., Biology, 1998, Laurentian University). As a tender undergraduate, I was already proficient with machine learning and multivariate statistics. Before the end of my Masters degree, I was conducting research using supervised learning, clustering methods and relational databases while also teaching these skills to other students and researchers.

Later, as a student of the Graduate Degree Program in Ecology at Colorado State University (Ph. D., Ecology, 2005), I began training in the intersection of computer science and ecology. I learned how to model systems and train them with data. I learned Bayesian statistics and used approaches like artificial neural-nets to solve complex ecological problems. It's clear, in retrospect, that I was already a practicing data scientist working with environmental data. 

After graduating, I consulted on data-analytic solutions for university, government and private industry clients, lectured at two Canadian universities and was hired as a Research Scientist at Landcare Research New Zealand Ltd. When I returned to Canada, I discovered our environmental research programs had been gutted (boo!), but that the emerging field of data science was what I had been training for since 1991. 

Now I'm helping a wider range of people do more with their data.