Building a data science portfolio

We were recently joined by Katie Schafer, VP of Advanced Analytics at Beam Dental, to discuss the most important things going on with data science leadership.

Great tips & resources shared for this question: What can I do to be able to present my skills and build a portfolio if I’m not able to share my work?

➕Many people expressed that they are in this position.

Katie: Is it possible to simulate something akin to some of the data you would use? For project portfolios, submitting the actual work is not something that I’ve seen often.

In interviews, you need to be able to discuss the work. Describing the projects is really tough because you want to say something meaningful but you don’t want to be too specific. Having a role play conversation with yourself on questions you’re getting & practicing answers that are more generalized can be helpful. Take one specific problem, translate that to an abstract problem that you tackled with statistics and programming.

Javier: I’ve been in a similar boat. There’s a package called synthpop: https://lnkd.in/g_paFGNB, which helps take actual data points and simulates them to make a completely synthetic data set.

When I was interviewing for my job now I built a shiny app that I deployed to a free shinyapps.io. I styled the whole app to be consistent with their brand. I don’t attribute that alone to getting the job, but the interviewers were super impressed. The ability to change out the theme is so easy, so for anyone who’s trying to get a job this could be an easy way for you to have something that you can change whenever you interview with a new company.

Rick: If you’ve ever worked with a designer – they have a template and they’re not just creating everything from scratch. If you have a nicely organized project as a data scientist, you’re showing your skills as a software engineer.

Zac: I do a lot of personal projects because I don’t use R at work. For these projects I focus the topic on what skills I want to show off. I’m looking to start my career, so I write a blog & include reasons why I did something. I think this makes it a lot easier to share what I’ve done https://lnkd.in/gzhwuCqw

Libby: For me with portfolio work, it’s been difficult because sometimes my contributions are one algorithm inside a larger shared project, so I stick to descriptions, talking about what I did and why I did it, what the result was.

Larry: I describe the topic and present the deck. Sometimes I just make fake data, but talk about the steps I took.

Katie: Some of my richest connections have also come from speaking. R-Ladies has been a great starting point for that. A lot of meetups have gone virtual so you can now join a chapter even if you don’t have one in your city.

Jiwan: Maybe start with a 5 min lightning talk with a topic you’re excited about!

Other resources shared during the chat:

Prabha: Technical debt in ML systems – https://proceedings.neurips.cc/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf

Rachael: R community explorer app: https://benubah.github.io/r-community-explorer/rugs.html

Javier: GitHub for the {bslib} app, feel free to clone as you see fit: https://github.com/JavOrraca/bslib_demo_shiny

Jobs shared during the chat:

Niklas: Several data science roles at my company (sustainability SaaS). 2 data engineers, 1 data analyst, 1 data scientist – https://higg.com/careers/

Jill: We are hiring for a Data Analyst role here at Viemed. We are a healthcare company and we LOVEEE DATA. https://viemed.apscareerportal.com/jobs/1338665/apps/new?embed=1