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Chris Comiskey, PhD

Cell: 303-638-2401

I am a statistician, data scientist, and R programmer with problem-solving, critical thinking, and communication skills. I carefully assess and articulate project goals, process data with tidyverse packages, conduct appropriate statistical analysis, create visuals with ggplot2, write reports with R Markdown and LaTeX, and present results with Beamer slides.


Statistical Analysis

  • Bayesian methodologies, including hierarchical models
  • Generalized linear models, including logistic regression
  • Design and analysis of experiments
  • Spatial statistics, including Gaussian Random Fields
  • Survival analysis, including Cox Proportional-Hazard models
  • Time series, including autocorrelated hydrologic series
  • Machine learning, including classification with decision trees
  • Graphics, plots, visualizations with ggplot2

Data Scientist Open Data Group, 9/2017 - Present

  • Predict mechanical failure probabilities with survival analysis decision trees
  • Predict macroeconomic indicators with ARIMA time series modeling
  • Clean, process, and wrangle messy big data, with tidyverse packages
  • Scrape web data with rvest, httr, jsonlite, etc.
  • Develop R packages for clients, using devtools, roxygen2
  • Write R Markdown reports, give LaTeX Beamer presentations
  • Develop R SDK components for use with ODG software REST API
  • Conduct literature reviews of latest machine learning techniques
  • Use Git, GitHub, Bash, MySQL, Python, HTML, Docker

Research OSU, 2013 - 2017

  • Developed variable-resolution heat maps for spatial data
  • Developed R package varyres for implementing variable-resolution heat maps
  • Developed interactive heat map confidence intervals for spatial estimators
  • Developed R package mapapp to create interactive heat map confidence intervals with RStudio’s Shiny
  • Modeled spatially correlated Bernoulli random variables with Bayesian hierarchical logistic regression (with GRF) model
  • Estimated “Effective Sample Size” for highly autocorrelated hydrologic time series, using AR(1) models
  • Thesis: "Take me out to (analyze) the ballgame : Visualization and analysis techniques for big spatial data"

Teaching 2010 - 2011, 2013 - 2017


Additional Tools of My Trade

  • dplyr for data manipulation
  • shiny for interactive-visual web applications
  • stringr, readr for string manipulation
  • lubridate for working with dates
  • rstan for Bayesian modeling
  • fields for spatial statistics
  • spBayes for spatial Bayesian modeling
  • INLA for numerical approximations in Bayesian modeling
  • mapapp for interactive heat map confidence intervals (aut)
  • varyres for creating variable resolution heat maps (aut)
  • rpart, LTRCtrees for survival analysis trees

PhD, Statistics 2017

Oregon State University

M.S., Statistics 2014

Oregon State University
Provost's Distinguished Graduate Fellow

B.S., Mathematics 2007

University of Colorado Denver