If you’re here, you definitely have heard about data science and you might wonder what data scientists really do? There is no good answer to this question! Data science is a relatively new field that was coined in 2008 by D.J. Patil, and Jeff Hammerbacher, then the respective leads of data and analytics efforts at LinkedIn and Facebook. As the field Is getting more mature the definition of data science changing drastically. The plot below used to be a popular way explaining what data science is. A data scientist used to be someone who knows a bit of math, , machine learning, statistics, programming and some domain expertise.
Nowadays, new jobs such as machine learning scientist, data engineer, applied researcher and … have popped up affecting what we expect from a data scientist. Today, “more than anything, what data scientists do is make discoveries while swimming in data. It’s their preferred method of navigating the world around them. At ease in the digital realm, they are able to bring structure to large quantities of formless data and make analysis possible. They identify rich data sources, join them with other, potentially incomplete data sources, and clean the resulting set. In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data” .
What makes data scientist different than data analysts?
Data analyst and data scientist skills do overlap but there is a significant difference between the two. Both the job roles require some basic math know-how, understanding of algorithms, good communication skills and knowledge of software engineering.
Data analysts are masters in using tools to slice and dice the data. With some level of scientific curiosity data analysts can tell a story from data. A data scientist on the other hand possess all the skills of a data analysts with strong foundation in modelling, analytics, math, statistics and computer science. A data scientist is expected to generate their own questions while a data analyst finds answers to a given set of questions from data. A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data.
But we would say the dominant trait among data scientists is an intense curiosity-a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested. This often entails the associative thinking that characterizes the most creative scientists in any field. For example, we know of a data scientist studying a fraud problem who realized that it was analogous to a type of DNA sequencing problem. By bringing together those disparate worlds, he and his team were able to craft a solution that dramatically reduced fraud losses .
Why data science is getting a lot of attention?
Data is considered as modern gold . The sudden appearance of data science on the business scene reflects the fact that companies are now wrestling with enormous amount of data that comes in varieties and volumes never encountered before; they need to extract information from that data to take actions and benefit from. Many organizations store multiple petabytes of data and the data most critical to their business resides in forms other than rows and columns of numbers. Those organizations are in desperate need of data scientist to go through their data and make sense of it to stay ahead of their competition.
What it means for you?
If “sexy” means having rare qualities that are much in demand, data scientists are already there. They are difficult and expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren’t a lot of people with their combination of scientific background and computational and analytical skills. It’s a great time to enter the market and become a data scientist so hurry up; if you have the foundations, gain the skills you need to be a good data scientist and start a sexy career!
- “Thomas H. Davenport and D.J. Patil, Harvard Business Review, Data Scientist: The Sexiest Job of the 21st Century”
- “The Economist , The World’s Most Valuable Resource is no Longer Oil, but Data”
Originally published at https://mentocta.com on June 23, 2019.