Data Scientist at Royal Bank of Canada. Part time PhD Candidate in Biostatsitics.
less than 1 minute read
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I’m very proud to say I have contributed this example to PyMC3’s documentation. It details how to compute posterior means for Gelman’s rat tumour example in BDA3.
Hoping to contribute more material to the library in the future.q
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Its late, I can’t sleep, so I’m writing a blog post about the optimism corrected bootstrap.
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Prior to the pandemic, my school’s gym would tweet out how many people were in the weight room at a given time. This was useful for an instantaneous understanding of how busy the gym was, but was not useful if you wanted to answer how busy the gym might be later. During my PhD, I managed to create a little python script to scrape some tweets, extract the number of people in the weight room, and model the data with a linear model. The model did OK, but I wanted to take it a step further and estimate the effects of days of weeks, months, special events, and even weather (because, as the gym’s manager told me when I met with her, the weather is a major factor in people going to the gym).
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On September 21st, 2021 I received an email from Tommy Caldwell, author and owner of Hybrid Fitness in my hometown of London Ontario, with the subject line “COVID-19, Kids, and Vaccines: A difficult decision for parents to navigate”. The email was sent from Hybrid Fitness’ email address (which I had subscribed to sometime in 2018, in the first year of my PhD). In that email, Mr. Caldwell acknowledges that vaccinating is a “no-brainer decision” and professes he is an inexpert in COVID19, science, and research, yet continues on to interpret statistics from a clinical trial intended to evaluate the vaccine against COVID19 in persons aged 12-15 years.
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I “left” (I say left in quotations because I’m still working on my Ph.D part time) approximately 3 months ago. That is a bit of a milestone. It is a quarter of a year working at a senior-ish level as a data scientist at a national bank. I know a lot of PhDs, especially in quantitative disciplines, are thinking of making the jump from academia to industry. This sequence of blog posts is not advice on how to make that jump, but rather to document one perspective on what that change entails.