Event data pervades applications across nearly any industry, be it failure data from a pump, a customer booking a hotel room, or defaulting on a loan. However, many professionals in the analytics field may not be familiar with the wealth of analytical methods that can be applied to these data.
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With two decades of experience in data science and statistics, Thomas is a highly experienced Data Scientist. His areas of proficiency include predictive and explanatory modeling, time to event analysis, inferential analysis, reproducibility, and data visualization, which he applies across various disciplines such as people analytics, mining, environmental health and safety, and technology effectiveness evaluations.
Having previously served as an applied statistician in cancer research and progressing to a data scientist and principal data scientist, Thomas has had a diverse career journey within the analytical domain. One of his core principles lies in promoting data and statistical literacy, and emphasizing the importance of evidence-based decision making within organizations.