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With the ever-expanding collection of information across all areas of life, the work of handling, analysing and using data has truly taken flight in the last decade. So has the professional field of data science, which encompasses the wide range of efforts to extract useful and valid knowledge from data.

The knowledge and skill underpinning data science are sourced from a range of core academic disciplines in the mathematical and computer sciences, including mathematics, statistics, machine learning, artificial intelligence, as well as many other disciplines.

This Review, initiated by the Australian Mathematical Sciences Institute (AMSI) and the Statistical Society of Australia (SSA), illustrates the central role that mathematics and statistics skills contribute to Data Science degrees at Australian universities. It also seeks to understand the needs of employers of Data Scientists, and how data science education at university level could be improved to better meet current and future industry needs.

Some of the key findings revealed in the report include:

  1. Data science is one of the fastest growing occupations in Australia, and there is unmet demand for well-trained data scientists across academia, research and industry.
  2. Senior secondary school mathematics is important preparation for entry into data science courses, and vital to grow the future data science workforce.
  3. Better connection between industry and universities is needed to support the growth of data science. This includes internships and work-integrated learning, research training events, career education, and facilitation of a community of professionals.

Given the significant demand for data science upskilling in the Australian workforce, AMSI Director, Professor Tim Marchant, indicates the importance of this review in the current climate.

“Data science is now an officially recognised occupation in Australia and is ranked in the top five most in-demand and highest paying jobs, with the global market for data scientists projected to grow almost 10-fold in the next five years. This report defines and describes the key role that the mathematical sciences play in developing data science skills to support the increase of student and employer interest in the Data Science discipline,” Professor Marchant said.

This Review, chaired by Distinguished Professor Kerrie Mengersen, Director of the QUT Centre for Data Science shows that it’s time that university data science courses have their own separate Field of Education, and that any data science degrees should include a certain level of statistical content.

“It’s time we treated data science like a grown up. It needs to go out on its own. It needs to move out of the house, especially when you consider it lives in many different houses, or in its case, schools depending on which university you’re talking about,” D/Prof Mengersen said.

“As a statistician, I can’t stress how important it is that any data science education include a certain level of statistics with it. Without that knowledge, we would be sending data scientists out into the wild without a very important skill set.”

The report constitutes a comprehensive review of data science in Australia and encompasses university education in data science as well as industry and government requirements for data science professionals.

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