Director of Customer Data, Data Science

Cafeyn

. Define and implement Cafeyn Group's Customer Data strategy aligned with business priorities and growth ambitions .

Posted 10/26/2026full-timeLondon • United KingdomLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and implementing customer data strategies, leading data science teams, and driving data-driven transformation initiatives. Proficient in data analysis, machine learning, and developing predictive models to enhance customer engagement and monetization.

Highest-signal resume keywords

Data AnalysisData Science LeadershipMachine LearningKPI FrameworksData Governance

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Hard Skills

Data AnalysisData ScienceMachine LearningPredictive ModellingCustomer SegmentationChurn PredictionPersonalizationRecommendation SystemsData ArchitectureA/B Testing

Soft Skills

CommunicationStakeholder ManagementTeam DevelopmentProblem-SolvingBusiness Acumen

Tools & Technologies

StatsigAI StrategiesData PipelinesAnalytics PlatformsDashboard Tools

Industry Keywords

Digital EnvironmentTechnologySubscriptionMediaData Monetization

About the role

Key responsibilities & impact

Define and implement Cafeyn Group's Customer Data strategy aligned with business priorities and growth ambitions
Represent Customer Data at Executive Committee level and translate strategic priorities into actionable data initiatives and measurable outcomes
Analyze customer behaviour, engagement, retention and monetization across B2C, B2B2C, B2B and CDS business models
Provide reliable dashboards, analyses and performance indicators to business teams
Structure KPI frameworks and performance funnels across Marketing, Product, Content and Business
Develop predictive capabilities, including churn prevention models
Establish data governance policies and drive data literacy and a data-driven culture
Define Cafeyn's Customer Data monetization strategy and identify first-party data, audience insight and segmentation opportunities
Build foundations for audience activation, including identity resolution, tagging, segmentation and measurement
Lead Data Science capability and manage 2–3 Data Scientists
Define the Data Science roadmap with Product and Technology leadership
Oversee AI-powered product capabilities including personalized recommendations, automated daily digest, semantic search and content discovery
Drive transition from experimentation to production and improve model performance
Own tooling and technical enablement for Statsig-based A/B testing
Partner with Product teams to measure AI and experimentation impact
Interface between Customer Data, Data Science and Data Engineering
Define data availability, reliability, integrity, completeness requirements, SLAs and access policies
Guide data accessibility, storage cost and platform scalability decisions
Lead and develop the Product Data and Data Science organization
Manage two Senior Data Analysts, one Machine Learning expert and 2–3 Data Science specialists
Establish priorities, ownership, delivery processes and performance expectations
Recruit additional talent and foster technical excellence, experimentation and continuous improvement

Requirements

What you’ll need

Significant experience in Data Analysis, Data Science, Machine Learning or a closely related data leadership role
Experience ideally within a digital, technology, subscription or media environment
Strong understanding of business performance analytics, customer behaviour, KPI frameworks and translating complex data into actionable business recommendations
Proven experience leading Data Analysis and/or Data Science teams
Ability to manage multidisciplinary teams and develop their capabilities
Strong understanding of machine learning and predictive modelling, including customer segmentation, churn prediction, personalization or recommendation systems
Demonstrated experience defining and implementing data strategies or data-driven transformation initiatives
Solid understanding of data architecture, data pipelines, governance and operational requirements of analytics at scale
Experience with experimentation frameworks, A/B testing and quantitative measurement is a strong advantage
AI knowledge and experience implementing AI strategies is a strong advantage but not a must-have
Understanding of first-party data, audience activation and data monetization opportunities is highly desirable
Strong business acumen and ability to identify commercial opportunities, challenge stakeholders and connect data initiatives to measurable business outcomes
Excellent communication and stakeholder management skills
Ability to engage effectively with executive leadership, technical teams and operational stakeholders
Hands-on mindset with ability to challenge technical and analytical decisions, contribute to problem-solving and drive execution
Willingness or ability to work in a hybrid arrangement in London

Benefits

Comp & perks

Pension plan – Standard pension contributions of 5% from the employer and 4% from the employee
Paid holiday – 26 days of paid holiday + 1 additional day off on your birthday
Mental health support – Access to Teale, a mental health platform where you can book appointments with psychologists and monitor your mental health
Hybrid policy – Work remotely up to two days per week
Cafeyn access – VIP access to Cafeyn, giving you unlimited access to all content on the platform
Team life – Four office meet-ups per year, bringing together international teams