Scottish businesses take on 100 data science placements

With 100 students placed this year, the running total for MBN’s involvement in the past three years stands at over 220 students placed.

MBN has developed several proprietary techniques to help identify and match MSc graduates to project opportunities within placement organisations and this, the firm claims, coupled with its approach to old school matching talent, is a key differentiator.

Director of client services Robin Huggins said: "At a time when technology seems to dominate, we focused on the notion that people buy people and adopted traditional techniques for what has been our largest and perhaps most impressive cadre of graduate data scientists.

The Data Lab chief executive Gillian Docherty said she had witnessed a huge take-up from organisations now exploring the use of data to drive value in Scotland and added: "We look forward to see what we can achieve in the future.”

With the growth in the use of data, combined with the fact that many ethical questions are now being asked about trust, privacy and security of data, MBN has observed that candidates are increasingly interested in the corporate values of the organisations in which they are being placed.

MBN’s own research also indicates a modest improvement in gender diversity of graduates wanting to be placed through the programme over the last two years. The firm is encouraging more women in data to participate at events as speakers and panellists.

MBN chair Paul Forrest concluded: “Scotland’s data sector benefits from better female representation than elsewhere in Europe but to improve overall we must continue to create a culture where access, ambition and progression is encouraged by business and academia alike. We continue to both lead and support initiatives and ventures that further enhance this and encourage others to do the same.

“Over the course of the next year our events programme will see us continue to focus on this with enhanced opportunities for all to participate in structured networking activities to help identify a new generation of women in data role models and mentors."