What Exactly Does a Data Scientist Do?

Data Scientists have been called many things: <ul> <li>“A Data Scientist is a statistician who lives in San Francisco”</li> <li>“Professional modellers, but not like that”</li> <li>“I get paid to Google Stack Overflow”</li> <li>“I sell magic to executives”</li> </ul> Or, my personal favourite: <ul> <li>“Data Science is statistics on a Mac”</li> </ul> As this smorgasbord of job descriptions shows, it can be really hard to get a clear picture on what a Data Scientist role actually involves day-to-day. Lots of the existing articles out there — while excellent — date from 2012–2020, and in a field that evolves as fast as Data Science these can quickly become outdated. In this article, my aim is to peel back the proverbial covers and give a personal insight into life as a Data Scientist in 2023. By drawing on my experiences of working in 3 different Data Science teams, I’ll try to help three types of people: <ol> <li>Aspiring Data Scientists: I’ll give a realistic insight into what the job involves, so you can make a more informed decision about whether it’s for you and what skills to work on</li> <li>Data Scientists: Spark new ideas for things to try in your team and/or give you a way to answer the question “So what is it you actually do?”</li> <li>People who work with (or want to hire) Data Scientists: Get to know what the heck we actually do (and, perhaps more importantly, what we don’t do)</li> </ol> <h1>It’s not all self-driving cars, ChatGPT, and Deep Learning</h1> The Head of AI at a large tech company once told me that the biggest misconception he encounters about Data Scientists is that we’re always building deep learning models and doing “fancy AI stuff.” Now don’t get me wrong — Data Science can get very fancy indeed, but it encompasses a lot more than Artificial Intelligence and its flashy use cases. Equating Data Science with AI is sort of like… <a href="https://towardsdatascience.com/what-exactly-does-a-data-scientist-do-42c53db57df5">Read More</a>