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We were recently joined by Sophia Tee, Senior Director of Data Science at Penguin Random House, to chat about marketing automation, the use of data science in publishing, and the transition from ID to manager in the realm of data science.
In this Hangout, we explore lots of topics, like how Sophia's team has automated the campaign creation process, reducing a two-week process to 30 minutes, while also improving campaign performance. That's pretty amazing! Needless to say, we had lots of questions.
She also had some great insights to share on the data science skills to strive for in the world of publishing as she experiences it. How organized is your code? It needs to be well-organized so that it "can be shared and understood by a lot of different people." She recognizes that not all data scientists have experience productionizing models, but that it's important in her line of work to be a full stack data scientist. Communication is paramount. Sophia says, "at the end of the day it doesn't matter how great your model is if you can't explain it. It's really hard to sell it. So, I think being able to speak in plain English about what you did, and what the outcome is, and what you expect people to do about it is really important." She stresses the importance of understanding the underlying data and the business context, too. Remember who you are speaking to and how your results relate to their KPIs. You'll have to listen in to hear more!
Resources mentioned in the video and zoom chat:
🔗 Sophia Tee on LinkedIn → https://www.linkedin.com/in/sophia-tee-7069b65/
🔗 Today's Top Books at Penguin Random House → https://www.penguinrandomhouse.com/interactive/todays-top-books
🔗 CloseRead Prize → https://posit.co/blog/closeread-prize-announcement/
🔗 Bioinformatics Training & Education Program from the NIH → https://bioinformatics.ccr.cancer.gov/btep/
🔗 Prefect AI workflow tool → https://www.prefect.io/controlflow
🔗 Pixi and uv integration blog → https://prefix.dev/blog/uv_in_pixi
We also talked about book recommendations! Of course we did, this was a discussion about Penguin Random House! Here are some of the data-flavored recommendations mentioned by the community live and in the chat:
📕 The Bayesian Hitman by Robert Kubinec: https://www.amazon.com/Bayesian-Hitman-Robert-M-Kubinec/dp/B0D6M4WNRZ
📘 The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives by Deirdre Nansen McCloskey & Steve Ziliak : https://press.umich.edu/Books/T/The-Cult-of-Statistical-Significance2
📙 The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century by David Salsburg: https://us.macmillan.com/books/9781466801783/theladytastingtea/
If you didn’t join live, one great discussion you missed from the zoom chat was about different perspectives and advice on transitioning from academia to industry (or the reverse!). Let us know below if you’d like to hear more about this topic.
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