Data Science, the polymath marriage of statistical modeling, computer programming and causal reasoning, developed as a field over the last 15 years. After an initial exponential growth until about 2019, the field has matured some. Now, according to the Bureau of Labor Statistics, there are more than 168,000 data scientists in the US. Assuming interest in Data Science is loosely correlated with the number of jobs in Data Science, we can estimate the years of experience of the average data scientist five years ago versus today. A typical (median) data scientists in 2018 was likely self-taught and had two years of experience. Now, the typical data scientist has around four years experience and likely has a master’s degree in the subject. That’s a huge difference.
As the average tenure of a data scientist team grows, the creativity and confidence with which they apply their skill grows as well. Instead of doing what is asked, they do what was desired. Instead of answering questions adjacent to the problem at hand because they are easy, they directly answer the question at hand (even if it’s hard, nay, especially if it’s hard). In order to remain in the field of Data Science in 2024, you have to think past the numbers and to what it means for the business and how it can generate value. People look to data scientists in boardrooms to help generate harmony around definitive courses of action.
On top of that, with the boom of generative AI, implementation of marketing experiments has never been lower (more on that later). As a result, in 2024, we hope for a surge of highly effective data-driven creativity from experienced data science teams. This growth will affect every part of business, not just marketing.