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2018 SIOP Machine Learning Competition Winning Submission Repository

The 2018 annual Society for Industrial and Organizational Psychology (SIOP) conference featured the first-ever machine learning competition. Teams competed for several months with various analytical techniques to predict turnover in a large US company. Winning submissions had to be done in open source and are posted in this repository. A more complete introduction as presented at the conference can be found here.


  • Predict voluntary turnover (who left) vs. who was still active as of December 31, 2014 at Eli Lilly


  • Data for 32,296 Eli Lilly employees active as of December 31, 2009
  • 162 predictor variables (demographics, location, job-related, job performance, etc.)
  • Training set (n = 24,205)
  • Test set (n = 8,091)
  • Evaluation metric: Cross-validated area under the ROC curve (AUC) statistic.


First Place: An Enriching Meal (Code)

Nick Koenig @ Walmart
David Futrell @ Walmart
Matthew Arsenault @ Walmart
Daniel Schmerling @ Capital One
Private Test Set AUC = .839

Second Place: Team DDI (Code)

Mengqiao (MQ) Liu @ DDI
Rachel King
Evan Sinar
Private Test Set AUC = .836

Third Place: ROC You Like a Hurricane (Code)

Erin Banjanovic @ HumRRO
Adam Beatty @ HumRRO
Ted Diaz @ HumRRO
Rod McCloy @ HumRRO
Colby Nesbitt @ HumRRO
Justin Purl @ HumRRO
Private Test Set AUC = .834

Fourth Place: Byte Monsters (Code)

Isaac Thompson @ Shaker
Scott Tonidandel @ Davidson
Private Test Set AUC = .834
Note: this code is split up into smaller chuncks for usability.


Dan J. Putka @ HumRRO
Alexander Schwall
Ben Taylor @ ZIFF