Hi everyone,

Last week I met with Jeff, an Interview Query premium member and future data scientist. Both Jeff and I live in San Francisco so we met up to talk about his job search and interviews. Jeff was fortunate enough to get several offers from different companies (with the help of Interview Query of course 😉) and was trying to decide how to value his options.

How should everyone value different offers? There's always salary and equity, the position at the company along with size and culture, and then arguably less important things like the commute to work and fringe benefits.

I joined a 10 person startup when I first started my career as a data scientist. The office was a studio apartment with the bedroom as a conference room, the ping pong table took up half of the overall desk space, and I learned quickly that "first data scientist" actually meant "full time data engineer with some data science on the side if you have time". There was no process, no testing, no hand-holding, it was get in and go!

When I think about weighing my values nowadays to picking jobs, I don't think I could work necessarily in that role again. I was heads down building algorithms and deploying models for such long periods of time that I had to force myself to walk around in the afternoon just to shine some sunlight on my face. But I learned a lot during that time and find the experience valuable today because every project I worked on at the startup was a priority of the company rather than something that would or would not see the light of day.

The learn versus earn argument cost benefit should always be a consideration. If you're coming into your first role as a data scientist, it's always best to pick the job that gives you the opportunity to learn the most to optimize your future earnings. Learning and earning are not always mutually exclusive, but it helps to go into each decision with a lens of weighing how much the role gives you the opportunity to work on improving the skills you want to fine tune, whether that's coding, communication, leadership, or being able to do a little of each.