“Statistics is the grammar of science.” – Karl Pearson
The global explosion of computerised statistics has given life to the Big Data Revolution. With the amount of data produced in the past few years alone far exceeding any human data previously recorded, it’s fair to say that statistics and Big Data are a BIG deal.
In the age of the Internet, it becomes critically essential for businesses and corporations in virtually every sector to harness data that can be used for analysis and discovery. Regardless of whether your profession lies in healthcare, communications, bandwidth or something more complex, the power of numbers and Big Data will allow you to make faster and smarter decisions.
But across the world, the industry lacks a constant source of qualified graduate talent. In 2015, the European Commission (EC) issued a report that explored the rising talent gap. The Commission claimed, at that time, that up to 77 percent of job openings remained vacant, predicting that a 160 percent rise in demand between 2013 and 2020 would make matters considerably worse.
It’s easy to stand back and quiver in fear at this significant shortage of skills. And while yes, this is something that needs to be addressed, it’s far more beneficial to view the universal shortfall as a playing field for specialist career opportunities. Jobs that require expertise in machine learning currently pay an average of US$114,000, with advertised roles for data scientists claiming $105,000 and data engineers earning approximately $117,000. It’s a career as lucrative as it is rewarding.
“A good data scientist is more than a mathematician, statistician or writer of algorithms – although these skills are obviously central to the role,” Nich Ismail of Information Age explains. “Data science is more than just number crunching: it’s the application of various skills to solve particular problems in an industry.
“This means you can’t just drop a statistics graduate straight into a data science position and expect them to start delivering insight from day one,” he adds. “The job requires far more theory – data scientists need to have a thorough understanding of the domains in which their insights will be applied. So on top of maths, a data scientist might also need a high level knowledge of supply chain, finance, logistics, human resources or any other line of business.”
The successful statistician displays many traits; from firm analytical and technical skill to a grasp of statistical methodology. But that’s only the start. You’ll also need to possess sound problem-solving capabilities, harnessing your specialised expertise so you can see the ‘Bigger Picture’.
If this is where you hope to be, you must be flexible and adept. It’s a fast-paced career in a field that’s constantly changing, so you need to learn how to react to rapid advances and developments. In this role, you’ll need to be able to multi-task and offer invaluable perspective, keeping up with current customer demand, on top of various projects and managers, to give your impact some weight. It’s not all about the numbers, for you will be compelled to master a complex business landscape to ignite career success.
“The democratization of statistics has opened up – and, indeed invited exploration of – new opportunities for statisticians to exert leadership, either informally or in a specific role such as team leader or manager of an organization,” an article from the American Statistical Association (AmStat) explains. “It requires you to have the strong personal, organizational, and visionary skills that characterize successful leaders.
“Our profession is constantly changing,” AmStat concludes, “as are the application areas in which you will be involved. You need to have the desire, and be able to make the time, to keep abreast of the latest developments in both.”
That’s where the University of Torino helps fill specific demand. Offering a two-year MSc in Stochastics and Data Science, the Italian institution empowers students to take the data realm by storm. The programme provides a contemporary education in probabilistic, statistical and computational methods, ensuring graduates leave with tools needed to thrive in a fast-evolving world.
The programme blends expertise from three of the university’s world-class research factions in Probability, Statistics and Computer Science. This unique merger of disciplines grants a firm bedrock of knowledge, covering key topics such as Applied Mathematics, Probability, Stochastic Modelling, Statistical Inference, Machine Learning and Computer Science.
Here, graduates leave readily equipped to enter top postgraduate programmes or service and industry companies. Students grow into confident, independent thinkers, possessing the essential skills and knowledge needed to perform mathematical modelling in uncertain conditions, as well as for the analysis of complex, high-dimensional data sets with a deep mathematical understanding of the underlying structures.
Students love that the course is taught entirely in English, providing a globally-recognised and accessible education for a highly competitive price. Offered in Italy’s beautifully vibrant city of Torino, students are surrounded by the Alps and not far from the Tyrrhenian Sea – a soulfully-stunning setting you won’t want to leave.