I was the “co-host” for a Data Science
Hangout a few weeks ago in May. These are weekly informal
conversations for data science leaders hosted by Rachael Dempsey and
RStudio. Thanks Rachael for inviting me! You can find the recording of
the event over on RStudio’s YouTube.
Rachael and RStudio did a fantastic job recapping the conversation in
the video description. However, I will add a rough outline of the topics
covered here.
1. Optimizing remote work
One difference between remote work and in-office work is the
reduction of thinking time away from screens. The book “Rest: Why You
Get More Done When You Work Less” by Alex Soojung-Kim Pang was
recommended, and I plan to read it (ironically when I have more time and
less work).
I shared some ideas for effective remote brainstorming (a topic I am
interested in). One of the great benefits of remote teams is the ability
to leverage technology to “level the playing field” for people of
different personality types, communication styles, and work
locations.
2. Getting
better data versus imputing missing data
There was a lot of good chat about imputing missing data and
recommendations for R packages. Unfortunately, the zoom chat is not
captured in the YouTube replay - one of the benefits of joining
live!
A good reminder here about not always trying to “fix” your analysis
but seeing if you can “fix” your data. Sometimes that missing data could
point to a problem in your data generation that is worth
investigating.
3. Conferences, tech,
and leadership styles
Someone asked about good conferences to attend. There were some
excellent recommendations and another data point that many people are
excited about the possibility of attending in-person meetings
again.
Tech stacks and teams switching from one set of tools (SAS) to
another (R). There were some great tips from others who have been
through this transition.
Resources to get started in data science. The recommendations
included finding something you are excited about and choosing something
to focus on.
Leadership styles and communicating with stakeholders. My advice was
to be opinionated and make it clear what you want your audience to take
away from any analysis/presentation/report.
4. Hiring (emphasis on remote
hiring)
My aspiration is to make our interview experience better for
candidates. I have been doing remote interviews for a while now, but I
still struggle. I hope to continue to innovate and draw from the
collective wisdom about what works and what doesn’t.
The YouTube video has an excellent summary of this part. It seems
the consensus is split on whether a technical component (live interview,
take-home assignment, etc.) is valuable or not.
One idea I like is to have the candidate bring their own example
code/analysis and walk through it as part of the interview.
Corrections
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Citation
For attribution, please cite this work as
Walsh (2022, June 18). Alice Walsh: Hanging out with data people. Retrieved from https://awalsh17.github.io/posts/2022-06-18-data-science-hangout/
BibTeX citation
@misc{walsh2022hanging,
author = {Walsh, Alice},
title = {Alice Walsh: Hanging out with data people},
url = {https://awalsh17.github.io/posts/2022-06-18-data-science-hangout/},
year = {2022}
}