Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Quant’s Dilemma: Subjectivity In Predictive AI’s Value
 Originally published in Forbes, September 30, 2024 This is the...
To Deploy Predictive AI, You Must Navigate These Tradeoffs
 Originally published in Forbes, August 27, 2024 This is the...
Data Analytics in Higher Education
 Universities confront many of the same marketing challenges as...
How Generative AI Helps Predictive AI
 Originally published in Forbes, August 21, 2024 This is the...
SHARE THIS:

2 years ago
Is Data Scientist Still the Sexiest Job of the 21st Century?

 
Originally published in Harvard Business Review, July 15, 2022. 

Ten years ago we published the article “Data Scientist: Sexiest Job of the 21st Century.” Most casual readers probably remember only the “sexiest” modifier — a comment on their demand in the marketplace. The role was relatively new at the time, but as more companies attempted to make sense of big data, they realized they needed people who could combine programming, analytics, and experimentation skills. At the time, that demand was largely restricted to the San Francisco Bay Area and a few other coastal cities. Startups and tech firms in those areas seemed to want all the data scientists they could hire. We felt that the need would expand as mainstream companies embraced both business analytics and new forms and volumes of data.

At the time, we defined the data scientist as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data.” Companies were beginning to analyze voluminous and less-structured data like online clickstreams, social media, and images and speech. Because there wasn’t yet a well-defined career path for people who could program with and analyze such data, data scientists had diverse educational backgrounds. The most common qualification in our informal survey of 35 data scientists at the time was a PhD in experimental physics, but we also found astronomers, psychologists, and meteorologists. Most had PhDs in some scientific field, were exceptional at math, and knew how to code. Given the absence of tools and processes at the time to perform their roles, they were also good at experimentation and invention. It’s not that a science PhD was really required to do the work, but rather that these individuals had the rare ability to unlock the potential of data, wading through complex, messy data sets and building recommendation algorithms.

To continue reading this article, click here.

 

3 thoughts on “Is Data Scientist Still the Sexiest Job of the 21st Century?

Leave a Reply