Chris Comiskey, PhD
Cell: 064-916-1452
Email: cwcomiskey@gmail.com
Statistician-Data Scientist with experience applying statistical and machine learning models to big data for forecasting, optimization, and decision-making.
- Experience
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Senior Data Scientist KPN, 2/2020 - Present
- Product development, for Financial Insights & Analytics in Group Business Services
- Anomaly detection with Random Cut Forest, for fraud detection
- Cashflow forecasting for Corporate Control
- Custom algorithm development for churn cycle forecasting
- Statistical analysis of risk assessment with random forest classifier
Senior Data Scientist Anchormen, 2/2019 - 1/2020
- Senior Data Scientist at adidas, Digital Advanced Analytics, EU eCommerce
- Delivered probabilistic demand forecasts impacting €100m in intake quantity (GAS models)
- Improved purchasing strategy with Optimal Overbuy methodology
- Developed Hierarchical Sampling technique for new-article demand forecasting
- Preseason demand forecasts impacted €70m in EU eCommerce intake quantity
Data Scientist ModelOp , 9/2017 - 11/2018
- Predicted mechanical failure probabilities with Survival Analysis decision trees for Ingersol Rand
- Predict Consumer Price Index with ARIMA models, for Exos Financial Services
- Develop decision tree/random forest R package for Prudential Financial
- Scrape web data for Exos Financial
- Survival Analysis decision tree Literature review for Ingersol Rand
- Write R Markdown reports, give LaTeX Beamer presentations
- Develop R SDK components for software product REST API
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
- Introductory Math Instructor, Community College of Denver
- Graduate Teaching Assistant, OSU Statistics Department
- Consulting, OSU Student Consulting Services
- Course development, OSU Data Analytics M.S.
- Education
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PhD, Statistics 2017
Oregon State University
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M.S., Statistics 2014
Oregon State University
Provost's Distinguished Graduate Fellow -
B.S., Mathematics 2007
University of Colorado Denver
- Supplementaries
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References
Websites