3. Results and Interpretation
Once you understand your data, that you have the full picture (or at least the closer vulgarization of what the truth would be), we want to share our findings with our peers. In science, we do so by the mean of presentations in symposium or scientific papers. Of course we could have feedbacks from our supervisor or reviewers, but they usually take ages to come and they are also mostly a one-way discussion. Meanwhile in tech, you will have to present your findings to people that do not have the same background as you do. Being excited about using that specific statistical technique of clustering because it was the exact use case (nope, that never happened to me…) will not make them as excited as you are.
You will need to work on what is the core take away from your findings.
That essentialist approach led me to make very simple figures with at the most 2 metrics in them. Then I had to present in person the results which led me to work on how to express myself for a more general audience.
With a simple approach, I realized also that I needed to look at the simple questions first, the “quick wins” as they say, that would then lead me towards more detailed analysis.
Of course, all of the above points can be found in academia, but in the tech industry, you have to do some studies from the ground up every month (sometimes every week depending on the project). In academia, you are the expert of your field, but you only focus on it and rarely venture elsewhere. You may have a couple of presentations a year and at most you are working on 1 to 3 paper a year. In the tech industry, you have reports to give every week. One day you can work on the acquisition cohorts of Whales (high-spending users) and the next you have to create a forecasting function that will identify potential users that will churn (un-subscribe/cancel or leave the product). The presentations are every month or even every week. So yeah, the pace is much more dynamic in the tech industry but also, you learn so much more, faster.
I know there are a lot of us who spent quite some times in academia who could not pursue it. Whether it was because your supervisor had a different agenda, you were sick of struggling to be able to afford a decent life or that there were no opportunities where you lived, it is not the end of the world. I found all the things that I loved in science in the tech industry. Flexible hours, creating your own projects, being responsible for your budget (in time) and sampling tools (homemade functions, third-parties solutions), the thrill of the investigation, and, in the end, presenting your results to your peers and have feedback on the spot that will lead to further studies.
In the meantime, nothing stops you from volunteering in an association. I realized that I had a better impact on the planet working in a marketing company but volunteering at picking trash while running in the forest than doing Arctic bio-geo-chemical modeling… So, do not hesitate to take a leap of faith, you have nothing to lose and only all to gain.