Data Intelligence Manager

Responsibilities

• Lead the creation of recurring and ad-hoc analyses: consumer behaviour, funnel performance, channel efficiency, journey optimisation opportunities, market trends, competitive benchmarking.
• Coordinate development and maintenance of advanced models (e.g., churn prediction, LTV forecasting, propensity scoring, recommendation algorithms), employing AI and machine learning techniques.
• Develop and implement experimentation frameworks (A/B testing, multivariate tests) in collaboration with activation teams.
• Scout and evaluate emerging analytics tools that use artificial intelligence, translating capabilities into scalable, business-ready use cases.
• Synthesise findings into compelling presentations, reports, and recommendations for senior leadership and marketing peers/teams.
• Proactively identify and investigate growth levers or risks through exploratory analysis, including opportunities to improve the customer journey and channel performance insights.
• Support strategic planning cycles with data-backed scenarios and forecasts.
• Partner tightly with the Data Product Manager on prioritisation and productisation of analytical features, including AI-powered capabilities.
• Collaborate with the Data Platform Manager on data improvements (via DBS and D&A) that unlock new analytical possibilities (e.g., enriched event data, cross-device identifiers, AI/ML-ready pipelines).
• Integrate insights into campaigns, support cross-functional initiatives, and lead analytical governance, team development, and guidelines (incl. self-service, rigour, and capability building).
• Serve as the go-to expert for growth-related questions, balancing depth of analysis with speed to deliver both quick-win insights and longer-term strategic studies.
• Translate complex analytical findings into actionable, non-technical narratives for executive and marketing stakeholders.

Requirements

• Minimum 8+ years in data analytics, business intelligence, data science, or intelligence leadership roles, with at least 3–5 years in a management position.
• Proven track record to translate analytics into growth impact in consumer-facing businesses (e.g., e-commerce, digital marketing, subscription services).
• Extensive experience with growth/marketing analytics (attribution, cohort analysis, customer journey mapping, personalization, channel performance analysis).
• Ability to enable evidence-based decision-making and foster a culture of analytical rigour, experimentation, and continuous learning.
• Background leading experimentation programs and influencing business decisions through data.
• Prior work in matrixed organizations with reliance on centralized data infrastructure and martech stacks.
• Hands-on analytical experience combined with strong people and collaborator leadership experience.
• Extensive global exposure across diverse markets and regulatory environments, with deep experience in consumer-facing industries and growth optimization methodologies.
• Expertise in statistical analysis, hypothesis testing, predictive modelling, and proficiency in tools/languages (advanced SQL, Python/R – pandas, scikit-learn, statsmodels).
• Experience with experimentation platforms, causal inference methods, data visualization (Power BI), and communicating insights to executive audiences; proven understanding of data flows and martech ecosystems.
• Familiarity with growth data concepts (multi-touch attribution, incremental, RFM), deep expertise in growth metrics (CAC, LTV, retention, funnels), knowledge of data privacy, and strong awareness of AI/ML-driven analytics with a relevant graduate degree.