Hi, I’m Greg Faletto.
I’m a data scientist working on getting key metrics from messy real-world data and using causal inference to measure the impact (lift) of ad campaigns. Previously I developed a methodology for A/B testing at Google, worked on machine learning at ZipRecruiter and Live Nation, and taught “Data Analysis for Decision Making” at the University of Southern California Marshall School of Business. I completed my Ph.D. in Statistics at the University of Southern California, where I wrote my dissertation on machine learning and causal inference. At USC I developed new machine learning methods for causal inference, estimating probabilities of rare events, and identifying the most important variables for predicting an outcome and wrote open-source software. My research has been published at the International Conference on Machine Learning and in the Proceedings of the National Academy of Sciences.
To learn more about me:
- You can download my resume here.
- My GitHub has code, written summaries of projects I’ve worked on, and slides from some presentations I’ve given. You can see some highlights on my code page.
- My research page has pdfs of all of my papers and preprints. You can also find a summary of my research on my Google Scholar profile.
- You can learn more about my professional background on my LinkedIn profile.
- Lastly, you can also get in touch by emailing me: gregory.faletto@marshall.usc.edu.