New avenues in the lucrative world of data science

What is a data scientist? The job title came out of nowhere as tech companies scrambled to find people to perform sophisticated analytical tasks over the past decade.

Six-figure salary reports abounded as companies vied for staff to slice and dice data in search of business lessons and emerging trends.

Recruiting firm PageGroup quotes annual salaries for data science work between £ 60,000-150,000, while warning that the job title covers a wide range of disciplines and responsibilities.

The line between data science and other activities such as data analysis has become blurred. James Hobson, a technology specialist at PageGroup notes that “there are several interpretations of what constitutes a data scientist.”

Whatever the qualification, the demand for personnel has exceeded the supply of those traditionally considered suitable for the job, usually candidates with a doctorate in computer science.

A 2020 report on emerging jobs in the United States from LinkedIn estimated that vacancies in data science were growing 37% annually.

So new operators are entering the field from unorthodox paths, aided by new software packages. Edward Green and Balraj Oates are two of them, although they both hesitate on the label of data scientist.

For Mr Green, his data science journey began at age 15 when he embarked on a series of extended stays at London’s Great Ormond Street Hospital while being treated for a complex medical problem that required three surgeries in two years and middle.

Most of us would rather forget such an ordeal. But Mr. Green remembers it as his gateway to a career working with technology. “The day I was operated on for the first time was the day the iPad was released,” he says.

He joined the hospital’s patient council and began capturing medical data on an iPad so it could be shown to patients. This experiment saw him enter directly into the world of computer science from school.

His surgeon had worked with McLaren, studying the application of F1 pit stop techniques to the movement of patients in and out of the ICU. So car racing and working at McLaren’s technology center just outside London, where car data is analyzed, was his next step.

McLaren uses data science software from US firm Alteryx which has developed its own self-service tool that can help people become data savvy.

For Mr Green, he trained him to juggle large amounts of data. In the case of McLaren this means 1.5 terabytes collected from each race. “Sometimes drivers feel they don’t need this data, but they do,” he says.

More business technology

Euan Davis studies the future of work at Cognizant, a technology services group. He says perceptions of the field have changed.

“Data science used to be a very dry job. He used to be seen as a nerd, but now he’s creative. Communication is important because you have to sell what you discover and that means telling stories about data.”

The future belongs to people with soft skills as much as it does to those who master rigid data analytics, he says.

“The position in data science is becoming a hybrid role. Now it’s about being a trusted advisor. The data scientist needs to be able to read data in a way that says something important to business executives.”

Data visualization tools, software that translates complex information into simple images, have changed the game of data science, says Davis: “The tools are becoming easier to use and more intuitive.”

Various data analytics companies like Tableau and Cloudera offer this type of program, translating information into simple graphs and icons for data scientists and others.

This approach recognizes that not everyone feels comfortable trying to extract clear information from the bewildering columns of figures that appear in large spreadsheets.

This new technology has created a gray area between the work of a data scientist and a data analyst.

Traditionally a data analyst might spend more time on routine analysis and providing regular reports. A data scientist would be responsible for how the data is manipulated.

Davis thinks this technology will prove reassuring in an era where “our jobs are changing around machines and we need to understand the data.”

Data science represented a dramatic change of direction for Balraj Oates.

It was introduced to the discipline via a competitive event, a hackathon where players analyzed data from global Covid cases to create regional comparisons of the pandemic.

Alteryx software allowed her to drag and drop icons representing data sets such as death rates.

Importantly, by manipulating icons rather than calculation pages, he could match the analysis speed of a statistician on his team. Compare working with data science tools with the use of a calculator.

This, he says, “started my journey into data”. He pushed her back into the workforce after a 12-year hiatus with three children.

Ms. Oates spotted the hackathon on the Women Returners website, which helps professionals get back to work after an extended career break.

She mentioned her experience in data science to another mother at her children’s school who turned out to be looking for a data development specialist.

Ms. Oates now applies her newfound knowledge in the financial services industry while her eldest son studies programming.

“It’s never too late to think about career development and it’s more accessible than you think,” says Ms. Oates, before adding how important it is to market yourself. “I got into this job through a conversation at the school gate!”