We are seeking a Marketing Analytics Manager to define and execute the analytical strategy for our global CRM program, supporting both Personal and Business customer segments. As a key member of the Marketing Analytics team, you will be responsible for scaling our lifecycle marketing capabilities through rigorous data analysis and hands-on project leadership.
This is a high-impact, cross-functional role that requires close collaboration with CRM, Product, Data Science, and Growth teams. You will own the global measurement framework for CRM, ensure the integrity of our data, and provide the strategic guidance necessary to prioritise high-value initiatives. This position also includes direct management and mentorship of two CRM analysts.
Key Responsibilities:
Serve as the primary analytics and business partner to the CRM function, providing strategic recommendations to drive customer acquisition, engagement and retention.
Own the global measurement framework for all CRM activities, including performance tracking, outcome forecasting, and incremental impact assessment.
Collaborate with CRM technology and Product teams to define data requirements and improve data quality, ensuring robust and reliable data for analysis and decision-making.
Lead performance analysis and insight generation for CRM stakeholders, translating complex findings into clear narratives and present strategic updates to Marketing leadership.
Contribute to the development and improvement of our segmentation, statistical models and analytical methodologies.
Support the evaluation of propositions and campaigns using rigorous statistical practices.
Manage and mentor two CRM analysts, fostering their professional development and building advanced CRM analytics capabilities within the team.
Required Qualifications:
4+ years of experience in marketing analytics within CRM/lifecycle marketing, including 1+ years in a manager capacity, with a proven ability to structure and solve ambiguous business problems.
Proven track record of influencing business strategy and driving measurable outcomes through data-driven insights.
Comprehensive technical skillset spanning insight generation, data modeling (dbt), reporting, and statistical testing methodologies (e.g., A/B testing, incrementality).
Extensive proficiency in advanced SQL for complex data manipulation in a data warehouse environment (e.g., Snowflake).
Experience with a programming language such as Python or R for data analysis.
Strong understanding of personalisation techniques and promotion frameworks.
Preferred Qualifications:
Professional experience in fintech, e-commerce, or a comparable high-growth technology industry.
Experience collaborating directly with Data Science teams on personalisation or predictive modeling initiatives.