Cambridge, GB, Onsite/Remote

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The Opportunity


In your role as  Lead Data Scientist, you’ll be responsible for the line management of a team of Data Scientists, acting as both a coach and a mentor. You’ll manage complex deliveries of Featurespace machine learning models into customer environments, managing client teams, and helping to accelerate critical work.

You’ll be involved in the improvement of internal processes, both operational and technical, and act as a senior point of knowledge and escalation of data science-related technical questions from the EMEA delivery team.

This role is based out of our Cambridge office and is a hybrid role, so you will ideally be comfortable coming into the office at least once a week. If you’re interested in the role but require more flexibility, please speak to us!


Day to Day

  • Developing and nurturing a team of Data Scientists
  • Managing team members on projects from the smallest to the very largest customer deployments
  • Ensuring that projects are run according to best practice as documented by the Data Science team’s ways of working
  • Monitoring the quality of the deliverables output by the Data Science team, ensuring that these are produced to an industry leading standard
  • Sharing knowledge of best practice relating to methods for data preparation, data visualisation, feature generation, feature selection and model governance
  • Working with customers to understand the opportunities and constraints of their existing data in the context of machine learning and predictive modelling
  • Improving team processes to increase team efficiency and quality of output
  • Providing input into future data science strategy and product development
  • Acting as product owner for critical tools in the data science workflow, ensuring that important functionality is delivered to specification by the responsible engineering team
  • Leading discussion with development teams to support and enhance the analytical infrastructure
  • Evaluating and improving the analytical results on live systems
  • Being an expert of industry data structures and processes
  • Develop expertise in the ARIC analytical tool stack and ARIC system architecture
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