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Data Scientist

Job Description

Exciting opportunity to join a large Government organisation to help lead multiple data projects using your exceptional experience in machine learning and NLP's.  Must be able to work 1 day a week either in London or Leeds.

We are looking for a Data Scientist who will cover multiple projects, with the aim of providing an envelope to call upon surge resource to the team.

Skills and Experience:

  • Experience of providing subject matter expertise and guidance to support in the development of clear, specific customer service requirements, managing scope changes to ensure successful project delivery.

  • Evidence of active engagement with stakeholders and negotiation skills and commitment to meeting stakeholder expectations.

  • Excellent oral and written communication skills, with the ability to choose content and style to suit the audience, including large groups. Able to communicate complex and technical concepts and issues to non-technical colleagues, customers, stakeholders and potential customers at all levels.

  • Significant experience of leading on a range of projects, including the allocation of work to other staff, to deliver quality outcomes to deadline and identifying risks.

  • Experience developing processes and procedures to ensure the effective, efficient and robust collection of data.

  • Experience of overseeing an analytical service delivery including the regular production of statistical products and publications.

  • Proven ability to collaborate and build relationships across organisational boundaries through complex service provision, identifying/managing demand in areas where there are shared and conflicting agendas.

  • Experience of working in and leading a multidisciplinary team using Agile methodologies

  • Proven ability to design new data products and analytical outputs that meet the needs of customers.

  • Experience of using statistical packages e.g. SAS, SPSS, Working with R or Python OR experience of using SQL

  • Proven ability to contribute to the building of long-term strategic plans & adapt technical thinking at pace in a fast-changing environment.


  • Expertise in the application of several supervised and unsupervised machine learning techniques such as classification (e.g. Random Forests, Support Vector Machine), regression (e.g. Ridge Regression, Lasso), dimensionality reduction (e.g. Principal Components Analysis, t-SNE) and clustering (e.g. KMeans, Hierarchical Clustering).

  • Awareness of techniques for conducting analysis with unstructured data, such as text (e.g. use of Natural Language Processing techniques) and image (e.g. working with DICOM1 data. 1 Digital Imaging and Communications in Medicine – a standard for handling, storing, printing, and transmitting information in medical imaging.

  • Understanding of neural networks / ‘deep learning’

  • Ability to understand Cognitive Artificial Intelligence (cognitive models mimic human thought processes) and semantic engines (information search and retrieval)

  • Experience of assuring quality and robustness of data products that incorporate Machine Learning methods, including ethical and legal considerations


  • Degree in an analytical subject (e.g. mathematics, stats, computer science)