From Python scripting to data engineering, MLOps and GenAIImage: Headway (Unsplash)In the 1980s, Wall Street discovered that physicists were great at solving complex financial problems that made their firms a bucket load of money. Becoming a “quant” meant joining the hottest profession of the time.Twenty years later, in the late 2000s, as the world was on the cusp of a big data revolution, a similar trend emerged as businesses sought a new breed of professionals capable of sifting through all that data for insights.This emerging field became known as data science.In 2018, I transitioned from academia to industry while completing my PhD in modelling frontier cancer treatments, working for one of the largest banks in Australia.I was joined by seven other PhD candidates from top universities across Australia, all specialising in different areas, from diabetes research and machine learning to neuroscience and rocket engineering.Fascinatingly, all of us eventually found ourselves working in the bank’s big data division — something we still joke about to this day.
Evolution of Data Science: New Age Skills for the Modern End-to-End Data Scientist | by Col Jung | Jul, 2024
