---
# System prepended metadata

title: Biotech Stack Dive

---

# Biotech Stack Dive

A podcast by Jesse Johnson & Eric J. Ma.

## Theme

A dive into how your company uses software to enable data flow between the bench/bedside and your data scientists.

## Guest List

We are keeping track of possible guests to invite on [a Google Spreadsheet](https://docs.google.com/spreadsheets/d/1KLxgVcQhWZ8_A2pTN1qbz0X2GspohBl9bVNegwSQw7o/edit?usp=sharing).

## Location

Let's try Jitsi? https://meet.jit.si/biotech-stack-dive-podcast

- Record to YouTube
- Keep track of how long we speak vs. guests' speaking time.
- Free service that is also open source.

## Questions

A suite of questions we can ask each guest.

1. Intro yourself (10 minutes.)
    1. Your current role at your company.
    2. How you made your way to your current role.
4. List out some of the most heavily used pieces of your tech stack (guest's choice on what they want to cover)
    1. Cloud compute
    2. app orchestration
    3. Data pipelines
    8. ML model serving
    9. Front-ends/UI toolkits
    10. DS tooling
11. How much of day-to-day work still runs on spreadsheets? If prevalent, what is your insight into the reason why spreadsheets are still so prevalent even in an age of democratized DS?
12. What are some of the thought processes that go into making decisions about what to automate and what to leave as-is? 
13. How should an organization break through outmoded practices w.r.t. data handling? (or) How did your org do it?
