Industry-wide professional standards are to be established for data science to ensure that the public can have confidence in how their data is being used.

The Royal Statistical Society (RSS) will be leading on the work along with the British Computer Society (BCS) The Chartered Institute for IT, the Operational Research Society (ORS), the Royal Academy of Engineering (RAEng), the National Physical Laboratory (NPL), the Royal Society and the Institute of Mathematics and its Applications (IMA), to collaboratively shape and develop the data science profession.

While the skills of data scientists are increasingly in demand, there is currently no professional framework for the field, noted a statement. The organisations involved aim to fill that gap by developing the necessary industry-wide standards. Starting with existing academic qualifications, the work will progress on to current professional standards. The group will work with universities to ensure that educational programmes deliver the right skills and knowledge for those looking to enter the profession.

The move follows recommendations in the Royal Society’s 2019 report on ‘Dynamics of data science skills’, that data science should be developed as a profession.

Rebecca George president of the BCS and the Chartered Institute for IT, said: “People are increasingly aware of data and how it is being used - data is a key part of our daily lives and we must ensure those using it are working ethically and to the highest standards.”

Stian Westlake, chief executive of the RSS, said: “You wouldn’t let a doctor perform heart surgery or an architect design your house without being confident they were working to the highest standards - we believe that people who deal with our data should follow equally high standards - and gain recognition for doing so.

Gavin Blackett, executive director of the ORS, added: “Data, where it’s come from, what it tells us and how it’s used in modelling, has always been a core part of ‘the OR process’ and we feel we have a lot to both contribute and learn as part of this important work to move data science professionalism forward to meet the needs of today’s world.”

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