Location: Manchester (Hybrid - 2 days onsite)Salary: £60,000-£90,000
The CompanyA global leader in multimedia content creation is expanding its advanced analytics hub to drive smarter, more personalised audience engagement. Operating across publishing, audio, and outdoor media, this organisation produces content for the UK's best-loved consumer brands. They are now recruiting a Data Scientist - Digital Audience Analytics to unlock deeper insights into how audiences interact with their digital ecosystem.
The RoleAs a Data Scientist - Digital Audience Analytics, you will be instrumental in understanding customer engagement patterns-how often audiences interact, where, and with what content. Your models and insights will inform programme targeting, communication strategies, and personalisation initiatives to maximise reach, loyalty, and conversion.
You will work closely with product, marketing, and content teams to ensure data shapes every customer touchpoint.
Key Responsibilities:-
Develop models to predict customer engagement patterns, channel preferences, and lifecycle behaviour.
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Analyse digital footprint data (page views, clicks, time spent, etc.) to uncover trends and opportunities for personalisation.
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Identify key audience segments based on behavioural, demographic, and transactional data.
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Support targeting strategies by developing recommendation systems and engagement scoring models.
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Present findings and actionable insights to product, marketing, and content teams.
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Help build experimentation frameworks to continuously refine audience strategies.
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Strong background in predictive modelling, segmentation, and customer analytics.
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Skilled in SQL, Python, and digital analytics platforms (e.g., Google Analytics, Looker).
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Experience working with digital customer journey data across web, mobile, and app ecosystems.
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Ability to communicate data-driven insights clearly to non-technical stakeholders.
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Familiarity with recommendation engines, user journey analysis, or churn prediction models is advantageous.
Register your interest by sending your CV to Daniel Abbasi via the apply link on this page.