Companies needed employees who could disassemble and analyze data sets in order to understand their business performance, learn lessons, and catch emerging trends. Salaries reach hundreds of thousands of dollars in some countries and companies.
Recruitment firm PageGroup says salaries for data science workers range from £60 to £150,000 gross annually. But he also states that the job description that comes with this salary covers wide areas and responsibilities.
The line between a data scientist and some job descriptions that require data analytics is a bit of a blur.
“There are different interpretations of what a data scientist is,” says technologist James Hobson of PageGroup.
Regardless of the job description, the demand for people to work in this field has exceeded the number of people traditionally considered to be able to work in the job. Those who fall into this category are generally those who specialize in computer science and have a doctorate.
LinkedIn’s 2020 emerging jobs report in the US showed that the demand for data scientists is increasing 37 percent each year.
As the demand increased, there were also those who fell outside the traditional definitions among those entering this sector. Especially those who have trained themselves with new computer software have entered the data science sector.
FORMULA 1 EXPERIENCE IN INTRODUCTION TO DATA SCIENCE
Edward Green and Balraj Oates are among those who chose this method. But both hesitate to describe themselves as “data scientists.”
Green’s data science adventure began at the age of 15. Due to some health problems he had as a child, Green underwent lengthy surgeries and treatment at Great Ormond Street Hospital in London for two, two and a half years.
Green remembers that period that many of us would like to forget, as a period when he built his career in technology:
“The day I had my first surgery was the day the first iPad was described,” he says.
Green joined the hospital’s patient council and collected medical data with the help of iPad to present to patients. This experience allowed him to enter the world of technology directly from school.
Green’s surgeon had previously worked with McLaren and examined how the technique of F1 breaks could be applied to the movements of patients moving in and out of intensive care.
Green’s next stop was motor racing and the McLaren technology hub just outside London. Here he analyzed the data of the cars.
At McLaren, Green used data science software developed by the US company Aleteryx. It is software that provides self-help tools that help individuals become data experts.
Thanks to this software, Green was able to work with large and large-scale data. For McLaren, 1.5 terabytes of data were collected after each race. “Formula 1 drivers sometimes think they don’t need this data, but they do,” says Green.
Euan Davis is an expert on the future of work at the technology services group Cognizant. He says perceptions in this area have changed:
“Data science used to be seen as a very boring, unpopular job. Now it is seen as a creative job. Communication is important because you have to be able to sell the data you uncover. That means telling the story about the data, what it means.”
What software tools are used?
Davis states that the future belongs to those with lighter and more “soft” skills as well as those who do the heavy lifting specializing in data analysis:
“The data science role is evolving into a more hybrid role. Now it’s important to be a trusted advisor. Data scientists must be able to read data in a way that can tell business executives what’s important.”
Data visualization tools and software that can transform complex information into simple images are changing the world of data science, Davis says: “These tools are getting easier and more intuitive to use.”
Data analytics companies like Tableau and Cloudera offer such programs. It turns information into simple tables and icons for data scientists and other beneficiaries.
Everyone may not feel comfortable enough to draw clear and precise information from the large data columns in the tables. This software is ideal for these people.
From software race to data science business
This new technology has created a gray area between the job of the data scientist and the job of the data analyst.
Traditionally, most of the data analyst’s time is spent regularly analyzing and preparing reports. The data scientist is also responsible for the ways in which data is processed (manipulated).
Davis thinks this technology is reassuring at a time when “our jobs are replaced by machines and we need to understand data.” Data science was also a turning point for Balraj Oates.
Oates’ departure to this world was accompanied by the Covid epidemic. In a hackathon, competitors were asked to examine data on global Covid cases and compare the epidemic by region.
Thanks to the Alteryx software, Oates drew and used symbols to represent datasets, such as death data. Oates was able to keep up with the analysis speed of a statistician on his team by processing symbols instead of pages of calculations.
Oates likens using data science tools to using a calculator and explains how his “data adventure” began. After raising his three children and being away from the business world for 12 years, Oates says he got back to work thanks to data science.
She saw the software competition on the website Women Returners, which helps professionals who take a long career break and want to return to work.
She also told a mother about her data science experience she met at her child’s school and said that they were looking for a data development specialist for the person she told by chance.
Oates, who got the job thanks to this, now uses his data experience in financial services, and his eldest child is studying coding. He also talks about how data science changed his life:
“It’s not too late to think about what can be done about career development. It’s a much more accessible field than you might think. I got into this job because of a chat at the school gate!”