To join future data science hangouts, add it to your calendar here: https://pos.it/dsh - All are welcome! We'd love to see you!
We were recently joined by Toby Hall, Executive Vice President and CIO at Delta Dental of Michigan, to chat about all kinds of things, including: data science team management, AI governance and the ethical use of data in healthcare, insurance data types and use cases, and hiring for traits vs. skills in data science.
In this Hangout, among other topics, Toby mentions Delta Dental's "guilty until proven innocent" approach to AI. This involves a two-stage approval process that critically examines use cases for ethical implications, data handling (ensuring data stays within dedicated tenants and doesn't train public models), and tool appropriateness. The discussion also touches on the regulatory skepticism towards AI from departments of insurance and the broader environmental considerations of AI use.
Toby also gives loads of career advice, but our favorite was his four-step process for managing a data team:
- Put the right people in the right role
- Give them the right vision of what you're trying to accomplish, ensuring it's clear and everyone is aligned on "what that is and why we're doing it"
- Give them the right culture to get it done
- Get out of their way!
Resources mentioned in the video and zoom chat:
🔗 Posit Conference → https://posit.co/conference/
🔗 Delta Dental Tooth Fairy Poll → https://www.deltadental.com/us/en/tooth-fairy/the-original-poll.html
🔗 TidyTuesday Data Repo (get your reps in!) → https://github.com/rfordatascience/tidytuesday
🔗 Resources for doing TidyTuesday stuff in Python (PydyTuesday?) → https://github.com/posit-dev/python-tidytuesday
If you didn’t join live, one great discussion you missed from the zoom chat was about the Delta Dental Tooth Fairy data, including its outrageously expensive rates and the humorous debate around the inflation of self-reported flossing data. Let us know below if you’d like to hear more about this topic!
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00:00 Introduction
02:28 "Tell us a little bit about your day to day, but also the data teams at Delta Dental of Michigan, what is the type of data that they work with, and what is it that they solve with it, or what decisions are made based on it?"
06:04 "What about third party data?"
07:57 "How do you all decide which language to use and for what applications?"
10:37 "How do you make sure your AI pipeline is accurate in the SQL and the regulation because you are working with health health care data?"
23:22 "What are some tips for leaning into those challenge assignments as the IC, the individual contributor?"
23:31 "How do you identify the challenge assignments? Like, how do you know this is the right thing with the stakes that are right to give to somebody?"
25:54 "Do you share your data as an API or for research?"
36:45 "Coming from a core statistical background, how much would you expect from a fresh data science graduate about statistical knowledge if you were an interviewer for a modeling role? Any specific concepts that you might ask them about in the interview?"
38:17 "How do you make sure your team stays current with new data science tools or skills or methods?"
40:18 "Did you have a ranking of necessary roles that you wanted to hire first, like data engineer versus data scientist or analyst or maybe dedicated reporting staff? And what tools or platforms did you consider essential from day one?"
43:53 "How much of your background in teaching high school students has spilled over into managing your team?"
46:21 "Do you have any advice for how someone could maybe emphasize those traits on their resume?"
49:19 "Do you have a piece of career advice that has either really, really helped you or that you try to give to everybody?"
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