Like many ambitious graduates at the start of their careers, Maria Jimenez believed that she would eventually need an MBA if she wanted a premier corporate job.

But she changed her mind after observing colleagues in her first job, working in the IT department of Bogotá-based pharmaceuticals business Tecnoquimicas.

The department was making strategic decisions for the company based on the data it collected on medical outcomes. Out of a team of more than 100 people, Ms Jimenez was the only one with an undergraduate business degree. 

“What they needed was someone with a business head who could also speak the language of software engineers,” Ms Jimenez says. So she ditched her plans to study for an MBA in favour of a place on a data science course.

Degree courses specialising in data science are booming, driven by excitement about the potential of data analysis in business, and fear of being left behind.

In the US, where applications for the traditional two-year MBA course have been declining for several years, masters degrees in data analytics are a growth market.

Seventy-four per cent of big data courses in the US reported increased demand last year, compared with 32 per cent of two-year, full-time MBA programmes, according to entrance exam body the Graduate Management Admission Council.

One in 10 women and 15 per cent of men interviewed last year by CarringtonCrisp, an education consultancy, for its annual global survey of prospective business school students said big data and business analytics courses were their preferred masters specialism.

Among men, big data was second only to finance in popularity, up from 13th place, in CarringtonCrisp’s last survey. For women, the shift has been in the same direction but less significant, moving from 13th to eighth place, behind management, accounting, human resources and psychology.

Demand for big data courses is driven by an increase in lucrative job opportunities advertised for people with such qualifications, according to Andrew Crisp, CarringtonCrisp’s co-founder.

“General Assembly, [the training business] which provides a lot of skills development in the field, often highlights in its emails the shortage of skilled data scientists in London,” Mr Crisp says.

“I suspect demand is simply a function of students seeing employers seeking to recruit people with these skills.”

Data from 2015 show the average pay across 48,347 data scientist roles and advanced analysts advertised in the US was $94,576, according to a report by PwC and the Business-Higher Education Forum. More than a third of those job postings required at least a masters qualification.

Ms Jimenez moved to France to study for her masters degree and is now midway through the big data analytics for business course at Lille’s Iéseg School of Management.

“I did not realise the dynamism of the data analyst jobs market until I started applying for roles,” she says, noting that many companies are looking for employees with her skillset.

Her tuition and living expenses are partly funded by a graduate student loan from the Colombian government, half of which would be converted into a grant if she returns to her homeland within three years of graduation.

Ms Jimenez believes she will stay in France, even if it means paying off her debt to the Colombian government in full, because positions advertised locally are so well paid. “This is a big investment, but I can see how it could pay off quickly,” she says.

A few miles away from Iéseg at the campus of HEC Paris, the first class taking the data science for business masters dual degree, with Ecole Polytechnique, has yet to graduate. But the schools have already received more than 1,000 applications for their second intake of 60 students.

“For a new programme, these kinds of figures are really promising,” says Julien Manteau, HEC’s director of strategy and global development.

New York University’s Stern business school has a strict limit of 70 students for its master in science of business analytics degree. Roy Lee, programme director, says that if the numbers were higher, the more “techie” students would feel less able to share insights with their business-minded classmates, which is crucial for breaking down barriers. “The idea is to get their two sides to share their different perspectives,” Mr Lee says. “Students are learning from each other about where and how to apply their skills.”

Sarah Laouiti is a full-time student on the masters degree in business analytics at Imperial College Business School, London. She studied international management as an undergraduate at Warwick Business School, but felt uncertain that this qualification would be sufficient, because she believes even previously well-paid roles in consultancy are becoming automated.

“I will definitely feel better prepared for the future world of work with a big data degree on my CV,” she says. “I don’t know what jobs will survive in the future but I am sure that those that do will involve using data.”

Data science v MBA courses

Prospective students are expected to show similar levels of academic attainment whether they are applying to business schools for a masters in data analytics or for MBA programmes. Where the paths differ is in the specifics of the curriculum.

Data science students take course modules that stretch their quantitative skills, such as advanced spreadsheet analysis and the concepts behind relational databases. These courses often also include lessons in how social media content is analysed and the techniques companies use in assigning credit scores to customers.

MBA students may touch on these issues but the focus will be on building leadership skills and understanding business through case study materials.

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