Grow your data science skills at posit::conf(2024)

August 12th-14th in Seattle

30 Jun 2022

Creating transparent & visible work

Rebecca Hadi

Head of Data Science at Lyn Health
We were joined by Rebecca Hadi, Head of Data Science at Lyn Health.
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Episode notes

We were joined by Rebecca Hadi, Head of Data Science at Lyn Health. Rebecca is passionate about improving healthcare using data science and machine learning.


At 19:11, Rebecca shared her approach to communication with transparent and visible work.


Here are 4 things they do on their team to create transparent & visible work:


1. Starting off with an open Data Science channel (different from their team channel) that’s open to the company.


For example, if we do an analysis for the sales team – we will post it in that channel and tag the sales team. That way anyone in the company can see the work. We keep conversations in the channel, rather than DMs. A lot of times someone else may be interested in that work.


2. We also have a Google sheet that we call our insight repository. We have that pinned to our channel so when we post analysis, we also put them in our insight repository with one row per analysis.


For example: in-patient mortality model, a headline, the link to the PDF, and the GitHub link. The insight repository has been very well received as a place that someone can start when they have a question.


3. I also host a weekly data science prioritization meeting and we use Monday as our project management tool.


This has been really helpful because in the past I’ve had some challenges with balancing requests from our clinical team versus sales team and understanding the priority. It can be hard to be that person in the middle. It’s a lot more productive when we can all have that conversation live. The sales team might say, “I need this for XYZ meeting” and you might have to say, “Ok, you know that’s going to push off these additions to the clinical dashboard.” Then the clinical team can weigh in, “We’re okay with that because of XYZ reason”


4. I’m also a really big advocate of a monthly all-employee call and I try to get air time there pretty frequently.


Initially it was level setting on “this is what data science is and how my team operates.” That has been successful for setting this idea of, “you are going to ask me something and I’m going to ask you the why behind it.” This helped set the precedent ahead of time where I’m not challenging an idea, but it will help my team produce better work if we understand why you care about this and how you are going to use it because that gives us context in decisions we need to make throughout the process.


A few resources shared too:


Javier shared: A resource that I just came across last week (def not something I do daily). if you’re wanting to collect / manipulate JSON data with R, Tom Mock has a super-easy-to-follow writeup with several different approaches:


Luke shared: Data is Plural newsletter is a decent off-the-beaten-path dredger of data sources:


Rebecca shared this book on management, The Hands-Off Manager:

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