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DataIQ Awards 2019 winner – Best data and analytics team (Data Titan): Channel 4 data science team

DataIQ Awards 2019 winner - Best data and analytics team (Data Titan): Channel 4 data science team

Data products created by the team are used across three major areas of Channel 4: for the consumer to drive the viewing experience based on clustering and personalisation; for clients via commercial and research teams to create new advertising products; and for the organisation itself via internal efficiencies and optimisation. To deliver against these needs, a wide range of data sets, tools and techniques are used, combined with a rigorous training programme and an enabling culture.

Team working and effectiveness are essential and based around three core values: continuous improvement, “doing what you say you’re going to do”, and supporting each other.  Lean techniques have been adopted, such as routine post-event wash-ups to understand and learn from anything that went wrong. Changes are adopted via this mechanism, rather than just through mandating new ways of working.

The internal training programme has seen multiple generations of practitioners evolve into highly-competent data scientists, even some who started out with no knowledge of coding. Learning and development is supported via theory, coursework, research, internal presentations, feedback, mentoring and project ownership. Time is also built in for experimentation and proof of value projects, which has led to the creation of the Contextual Moments advertising service, for example.

The health of individuals and teams also has a central role to play, especially by drawing on principles of happiness and work and the need for good relationships, autonomy, challenge and purpose. A weekly survey indicates team health and identifies any warning signs. As a direct result of seeing challenges around work-life balance, Channel 4’s data science team revamped its policy on flexible working hours. 

DataIQ Awards 2019
Year: 2019
Category: Best Data and Analytics Team

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