Names and details in this blog post have been altered to protect the privacy of its subjects.
I met my old professor, Dr. Perez, for lunch recently. We have kept in touch for many years since she taught me during my undergraduate studies, and she has been a good friend and mentor. We had not seen each other for a few years, but we have been in regular contact over phone and email, exchanging stories, updates, photos of her grandchildren, frustrations, thrills, and perspectives. It was nice to see her again.
I told her about the accomplishments and the struggles in my early career as a statistician so far. I am generally satisfied with how I have performed since my entry into the statistics profession, but there are many skills that I don’t have or need to improve upon. I want to learn distributed computing and become better at programming in Python, SQL, and Hadoop – skills that are highly in demand in my industry but not taught during my statistics education. I want to be better at communicating about statistics to non-statisticians – not only helping them to understand difficult concepts, but persuading them to follow my guidance when I know that I am right. I sometimes even struggle with seemingly basic questions that require much thinking and research on my part to answer. While all of these are likely common weaknesses that many young statisticians understandably have, they contribute to my feeling of incompetence on occasion – and it’s not pleasant to perform below my, my colleagues’, or my industry’s expectations for myself.
Dr. Perez listened and provided helpful observations and advice. While I am working hard and focusing on my specific problems at the moment, she gave me a broader, more long-term perspective about how best to overcome these struggles, and I really appreciated it. Beyond this, however, she told me a story about a professor of our mutual acquaintance that stunned and saddened me, yet motivated me to continue to work harder.
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