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Machine Learning Data Scientist - KTP Associate - Liberty IT
  • Python
  • Machine Learning
  • Excel
Queen's University Belfast
Belfast BT7
134 days ago

Queen’s University Belfast is one of the leading universities in the UK and Ireland, with a distinguished heritage and history. With over 24,000 students, 4,200 staff and an annual turnover of some £300m, Queen’s University Belfast plays a unique leadership role in Northern Ireland. As a member of the Russell Group of UK research-intensive universities, Queen’s University Belfast combines excellence in research and education with a student centred ethos. As a leader of Knowledge Transfer Partnership (KTP) development and delivery for 25 years, KTP is held in high regard within Queen’s and the programme has been the foundation for many research and teaching successes including 15 National KTP Awards. The KTP Programme has been helping businesses throughout the UK for over 40 years by recruiting suitably qualified graduates to take on a role that bridges academia and business.

As a KTP Associate you will have the opportunity to apply your academic knowledge to a real life challenge that delivers tactical change within an organisation. A KTP is the perfect launchpad, helping enhance your career prospects by providing you with an opportunity to manage a challenging project central to a business’s strategic development and long term growth. You will have access to a substantial training and development budget and take ownership of a project, with the added support and guidance of Queen’s world class Academics. Through the KTP programme we wish to recruit a highly skilled postgraduate to work in Liberty IT (Belfast) as a Machine Learning Data Scientist on a collaborative project with the Institute of Electronics, Communications and Information Technology (ECIT) at Queen’s over 24 months.

Based in Belfast, Liberty IT is a wholly owned subsidiary of The Liberty Mutual Insurance group. Liberty Mutual Group is fortune 100 Insurance company that sells Insurance worldwide in over 17 countries. Liberty IT is part of the Liberty Mutual technology department that builds and maintains technology solutions for Liberty's global business. We are technology experts, heavily involved in influencing the technology direction for the Liberty Mutual group and driving digital transformation across all business units. We specialise in innovation and introducing new capabilities to the wider organisation. Liberty IT (Belfast) want to develop significant capacity in data science in order to strategically lead the next generation of innovations in the insurance sector through data-driven technologies, and help Liberty Mutual reinforce and expand its position as a global leader.

Liberty Mutual seeks to exploit the field of AI to help drive efficiency within their core Claims and Underwriting value claims. The goal of this KTP is to use computer vision to drive efficiency and increase customer satisfaction.

The successful candidate must have:

  • Hold, or be about to obtain in July 2020, at least a 2.1 (or equivalent) in a Masters degree or higher in Computer Science, Mathematics or another quantitative field.
  • At least 6 months’ relevant work or research experience*.
  • Demonstrable proficiency in programming and experimental analyses with Python or R programming languages.
  • Proven knowledge of natural language processing, Artificial intelligence or machine learning.*
  • can include relevant experience gained through a student project, module, work placement or a higher degree.

For full job details and essential/desirable criteria please refer to the candidate information link on our website by clicking apply. For further information or assistance contact The Resourcing Team, People and Culture, Queen's University Belfast, BT7 1NN. Telephone (028) 9097 3044 or email on

The University is committed to equality of opportunity and to selection on merit. We welcome applications from all sections of society and particularly from people with a disability.

Informal enquires may be directed to Karen McGeough, email: or telephone: 028 9097 3970.

Additional contact person:

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