Director of Customer Data & Data Science Cafeyn

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Readly is now part of Cafeyn Group. With the acquisition of Readly's non-Nordic operations, Cafeyn further strengthens its position as the European leader in access to information – combining scale, technology, and deep local market expertise.

Together, the Group now operates across 15 markets, serves 2.5 million users, and provides access to more than 5,200 publications from 1,100 partner publishers.

To empower individuals with access to trusted, high-quality content that fosters personal growth and discovery. Whether it's through the comprehensive collection of news and features on Cafeyn & Readly, the digital publishing solutions of Milibris, the fun and educative content for children on Kidjo, or the collections for manga lovers by Mangas.io, Cafeyn Group stands at the forefront of digital content experiences.

If you're passionate about building strategic partnerships, driving commercial growth and shaping the future of digital media, we'd love to meet you.

As Cafeyn continues to grow, the Group is accelerating its transformation towards a truly data-driven organization, leveraging Customer Data and Artificial Intelligence to improve business performance, enhance product innovation and develop new revenue streams.

As Director of Customer Data & Data Science, you will define and lead Cafeyn Group's Customer Data strategy, transforming data into a strategic asset that drives business decisions, product development and revenue growth.

Reporting into the Group's leadership structure, you will act as the primary ambassador for Customer Data, working closely with the Executive Committee, Marketing, Product, Content, Business and Technology teams.

Your mandate will be twofold: maximize the business value of customer data and accelerate the development of AI-powered products.

Beyond delivering insights and tools, you will challenge existing business practices, identify opportunities for improvement and ensure that data becomes a driver of strategic decision-making rather than simply a reporting function.

You will lead the restructured Data Analysis and Data Science teams, establish the foundations for scalable Data adoption, and work closely with Data Engineering to ensure the reliability, accessibility and performance of Cafeyn's data infrastructure.

Your responsibilities

1. Define the Customer Data strategy and drive business performance

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

• Act as the primary representative of Customer Data at Executive Committee level, translating strategic priorities into actionable data initiatives and measurable business outcomes.

• Develop a comprehensive understanding of customer behaviour, engagement, retention and monetization across Cafeyn's B2C, B2B2C, B2B and CDS business models.

• Ensure that business teams have access to reliable, relevant and actionable dashboards, analyses and performance indicators to identify challenges, understand underlying trends and improve business performance.

• Structure KPI frameworks and performance funnels across Marketing, Product, Content and Business, identifying opportunities to optimize acquisition, engagement, conversion, retention and revenue.

• Develop predictive capabilities, particularly churn prevention models, to anticipate customer behaviour and enable proactive retention strategies.

• Challenge business stakeholders constructively, moving beyond a traditional internal service-provider relationship to become a strategic business partner who questions assumptions and helps identify new opportunities.

• Establish robust data governance policies, ensuring data quality, integrity, accessibility and consistent usage across the organization.

• Drive data literacy and foster a data-driven culture, empowering teams to incorporate data into their day-to-day decisions.

2. Develop the data monetization strategy

• Define Cafeyn's Customer Data monetization strategy, supporting the diversification of the Group's revenue streams.

• Identify opportunities to create value from first-party data, audience insights and customer segmentation, particularly in relation to advertising and B2B commercial offerings.

• Build the data foundations required for effective audience activation, including identity resolution, tagging, segmentation and measurement.

• Work closely with Marketing, Sales, Business and Content teams to translate customer insights into new commercial opportunities and scalable revenue-generating initiatives.

• Assess the potential of data products and services, ensuring that monetization initiatives are commercially relevant, technically feasible and aligned with applicable privacy and regulatory requirements.

3. Lead Data Science, AI-powered product innovation and experimentation

• Lead Cafeyn's Data Science capability, managing a team of 2–3 Data Scientists responsible for developing and deploying AI-driven product features.

• Define the Data Science roadmap in close collaboration with Product and Technology leadership, ensuring that initiatives address meaningful customer needs and deliver measurable value.

• Establish the processes, methodologies and operating conditions required to accelerate the delivery, deployment and continuous improvement of Data Science developments.

• Oversee the evolution of AI-powered product capabilities, including personalized recommendations, the automated daily digest feature, semantic search and future content discovery innovations.

• Ensure that Data Science initiatives are prioritized according to their expected impact, feasibility and alignment with Cafeyn's product strategy.

• Drive the transition from experimentation to production, improving delivery predictability, model performance and the operational impact of AI-powered features.

• Partner closely with Product teams to measure the impact of AI innovations on engagement, retention, customer satisfaction and business performance.

• Own the tooling and technical enablement of Cafeyn's A/B testing framework, using Statsig to support a scalable, quantitative experimentation capability.

• Work closely with Product teams, who own the testing strategy and prioritization, to ensure that the underlying tooling enables reliable experiments, robust statistical analysis and informed product decisions.

• Establish clear measurement practices to evaluate the impact of AI initiatives and experimentation on operational efficiency and product performance.

4. Partner with Data Engineering to build scalable data foundations

• Act as the primary internal interface between Customer Data, Data Science and the Data Engineering team, ensuring that the data platform meets current and future business needs.

• Work closely with Data Engineering leadership to assess whether the existing architecture can support Cafeyn's strategic ambitions, growing data volumes and evolving analytical requirements.

• Define data availability, reliability, integrity and completeness requirements, establishing clear service-level agreements (SLAs) and access policies.

• Ensure that the right data is accessible to the right teams, through the appropriate tools and within the required timeframes, from real-time applications to historical and cold-storage environments.

• Guide decisions around data accessibility, storage costs and platform scalability, ensuring that infrastructure choices support both advanced analytics and production-grade AI applications.

• Anticipate the data requirements of new business models, customer activation initiatives and AI-powered product features, aligning the data roadmap with the broader Technology strategy.

5. Build and develop high-performing teams

• Lead and develop the restructured Product Data and Data Science organization, bringing together complementary analytical, machine learning and product innovation capabilities.

• Manage a team comprising two Senior Data Analysts, one Machine Learning expert focused on predictive modelling, and a Data Science team of 2–3 specialists.

• Establish clear priorities, ownership, delivery processes and performance expectations across the teams.

• Foster collaboration between Data Analysis, Data Science, Data Engineering, Product and Business stakeholders.

• Develop the team's capabilities, recruit additional talent where needed and create an environment that encourages technical excellence, experimentation and continuous improvement.

What success looks like in the first 12 months

• A clear Customer Data strategy and Data Science roadmap: A defined roadmap aligned with Cafeyn's business priorities, including measurable objectives and a clear data monetization strategy.

• A stronger data-driven organization: Reliable KPI frameworks, actionable dashboards and performance analyses supporting Marketing, Product, Content and Business decision-making.

• A more effective retention strategy: Predictive churn models and actionable customer insights translated into measurable retention improvements.

• A structured Data Science capability: Clear prioritization, improved delivery predictability and successful deployment of high-impact AI-powered product features.

• A fully operational experimentation framework: Effective A/B testing tooling and processes enabling Product teams to make better-informed decisions.

• Scalable data foundations: Clear data quality standards, access rules and service-level agreements established in partnership with Data Engineering.

• Measurable business impact: Demonstrable improvements in customer engagement, retention, operational efficiency and the identification of new data-driven revenue opportunities.

Your profile

• Significant experience in Data Analysis, Data Science, Machine Learning or a closely related data leadership role, ideally within a digital, technology, subscription or media environment.

• A strong understanding of business performance analytics, customer behaviour, KPI frameworks and the translation of complex data into actionable business recommendations.

• Proven experience leading Data Analysis and/or Data Science teams, with the ability to manage multidisciplinary teams and develop their capabilities.

• A 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.

• A solid understanding of data architecture, data pipelines, governance and the operational requirements of analytics at scale.

• Experience with experimentation frameworks, A/B testing and quantitative measurement is a strong advantage.

• AI knowledge and experience in implementing AI strategies is a strong advantage but not a must-have.

• An understanding of first-party data, audience activation and data monetization opportunities is highly desirable.

• Strong business acumen, with the ability to identify commercial opportunities, challenge stakeholders and connect data initiatives to measurable business outcomes.

• Excellent communication and stakeholder management skills, with the ability to engage effectively with executive leadership, technical teams and operational stakeholders.

• A hands-on mindset: you can challenge technical and analytical decisions, contribute to problem-solving and drive execution rather than relying exclusively on your teams.

What will make you successful

You combine strategic vision, strong data expertise and a genuine business mindset. You understand that the value of data lies not only in its quality or technical sophistication, but in its ability to improve decisions, strengthen customer relationships, accelerate product innovation and generate new revenue.

You are comfortable operating at both strategic and operational levels: defining a vision with senior leadership, challenging business assumptions, structuring teams and processes, and ensuring that initiatives translate into tangible results.

Above all, you are a change leader who can bring people together around a shared ambition: making Customer Data and AI-powered products core drivers of Cafeyn's future growth.

Hiring process

1. HR Interview with one of our Talent Acquisition Manager (30’)

2. Hiring manager Interview with our Chief Strategy Officer

3. Case study

4. Peer Interview with our team

5. Last Interview

Perks & benefits of working at Cafeyn

• 🏥 Health insurance – Comprehensive health insurance coverage.

• 💆 Well-being allowance – €350 gross well-being allowance paid every December.

• 🧠 Mental health support – Access to Teale, our 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 our platform.

• 🪅 Team life – Four office meet-ups per year, bringing together our international teams to celebrate company updates and spend quality time together.

You don’t have to match all the requirements, if you feel this offer could be a great opportunity for you, reach out anyways! We hire based on talent and we promote inclusivity inside Cafeyn and strongly believe that our culture is strongest when it is the most diverse.