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Data Science Foundation

The University of Manchester is a member of the Data Science Foundation, a professional body representing the interests of people working in the Data Science sector. The Foundation brings together suppliers who offer a range of analytical and technical services in the Data Science sector and companies and individuals with an interest in the commercial advantages gained from data science. The foundation supports communication and knowledge sharing between members, educates people about the benefits of knowledge based decision making and to encourage firms to start using big data techniques. Current University members include universities from the UK and the US, and the Foundation boasts sponsors such as IBM UK Ltd., Eden Smith and Peppersack, and suppliers such as Inflexion Analytics, Privigo Ltd. and Hello Soda.

Benefits of membership

Students at the University of Manchester are encouraged to apply for Individual membership of the Data Science Foundation. Membership is free of charge and offers the following benefits:


  • Opportunity to become an active and high-profile member of the data science community
  • Collaborate on data science projects and research
  • Find out about new placement and employment opportunities
  • Publish a CV, and gain access to the jobs board
  • Offer services as an expert speaker on data science topics


  • The site hosts forums on a number of relevant categories, to which members can freely contribute by opening a topic and commenting on current threads
  • Ask for information and assistance

Personal Profile

  • Each member has a personal profile page, helping to build the reputation of the individual in the wider data science community by listing experience, education and interests.

Publish Work

  • Publish articles and papers and have others rate the work
  • Publish thoughts on specific topics and generate review and feedback
  • Compete in the Contributors League; all published items receive contributor points
  • Articles and papers highly rated by the community are published on social media

Published by

  • Each member has a ‘Published By’ page showcasing their work and how it has been rated


  • Each member manages their own data and published work via a secure dashboard


  • Communication is further encouraged through the screened ‘Contact a Member’ function, whereby email addresses remain hidden and secure

To visit the Data Science Foundation website please click here: