About Me

I’m a behavioral scientist and a data scientist. I aim to work at the top of my license and make the world a better place to live. I am interested in working for companies that have a positive social impact.

I hold a PhD in Psychology from the University of Guelph Applied Cognitive Science program, and a Master’s in Psychology with a concentration in Cognitive Psychology from Carleton University.

While I was a graduate student, I started to work as a freelance behavioral scientist and software developer for energy-conservation start-ups in Ontario (eMERGE Guelph, Greenbrain, Project Neutral). I continue to provide services to eMERGE.

Since graduating from my PhD program in 2017, I’ve been working full-time at healthcare start-ups, acting as a Research Scientist and a Quantitative Researcher – in practice, a combination of a Behavioral Scientist and a Data Scientist.

I’m proficient in R, JavaScript, and python, and I’m always learning new things so I can be a better scientist and programmer. In 2019 I completed two data science MOOCs to sharpen my skills in R and python: 1) the Data Science Specialization offered by Johns Hopkins University on Coursera (a 40-hour specialization), and 2) the Data Scientist with Python Track offered by Datacamp (a 100-hour specialization).

You can find the best examples of my work here on my Blog, on my Publications page, and at my GitHub.

Visual timeline

Code for the above visualization:

library(timevis)

data <- data.frame(
  id      = 1:10,
  
  content = c("BA in Psychology", 
              "MA in Cognitive Psychology",
              "PhD in Applied Cognitive Science",
              "Freelance Behavioral Science / Software Development",
              "Assistant Research Scientist @ New York University",
              "Research Scientist @ Datacubed Health",
              "Adjunct Professor in Applied Analytics @ Columbia University",
              "Quantitative Researcher @ Clover Health",
              "Data Science Specialization @ Coursera",
              "Data Scientist with Python @ Datacamp"),
  
  start   = c("2005-09-01", 
              "2009-09-01",
              "2011-09-01",
              "2014-01-01",
              "2017-02-28",
              "2017-12-31",
              "2018-09-01",
              "2018-11-15",
              "2018-07-01",
              "2019-12-01"),
  
  group = c(1, 1, 1, 2, 2, 2, 2, 2, 1, 1)
)

timevis(data, groups = data.frame(id = 1:2, content = c("G1", "G2"))) %>%
  setGroups(data.frame(id = 1:2, content = c("Education", "Positions"))) %>%
  setOptions(options = list(showCurrentTime = FALSE, orientation = "top"))