• Manage and evolve Airalo’s growth MMM portfolio - driving the existing market model from validation into a production-grade decision tool, and scaling to additional markets as growth ambition and data readiness allow. • Design and execute incrementality experiments (geo-holdouts, conversion lift studies, synthetic control, difference-in-differences) that calibrate the MMM and establish true causal impact of marketing spend across channels. • Evolve our attribution methodology: determine the right models and attribution windows for our purchase cycle, specify the data requirements, and measure the impact of tracking remediation on attribution accuracy. • Calculate and continuously optimize the CAC metrics (platform-reported, internally-attributed, incremental, and blended) and own LTV:CAC as a strategic KPI reported to leadership. • Build measurement literacy within the Growth and Acquisition teams: train stakeholders to interpret the LTV/CAC related metrics, understand the difference between attributed and incremental performance, and use self-service reporting with confidence. • Build and maintain the performance marketing reporting framework - with Analytics Engineering to ensure the underlying models serve both reporting and measurement needs. • Act as analytics partner to the Growth and Acquisition teams: translate business questions into measurement plans, deliver the analytics that inform spend decisions, and build self-service reporting that reduces ad-hoc dependency. • Drive adoption of measurement outputs-ensure MMM scenarios, incrementality results, and attribution insights translate into concrete budget allocation changes. • Contribute to the development of a unified decision framework that integrates signal health, attribution, and incrementality into budget allocation guidance with clear go/no-go criteria for scaling spend by market and channel. • Build institutional knowledge: document every experiment result, every MMM refresh, and every signal quality trend so that each quarter’s decisions are better informed than the last. • Collaborate with the Senior CDP Engineer and MarTech on the data and signal infrastructure that underpins measurement - defining what you need, so they can build it right.

• Desarrollo, mantenimiento y evolución de dashboards e informes en Power BI. • Modelado de datos para entornos de gran volumen. • Creación y optimización de medidas y cálculos utilizando DAX. • Transformación y preparación de datos mediante Power Query (lenguaje M). • Análisis de datos orientado a la toma de decisiones estratégicas del negocio. • Colaboración con equipos técnicos y de negocio para traducir necesidades en soluciones analíticas eficientes. • Asegurar rendimiento, calidad y escalabilidad de los modelos y reportes. • Documentación de modelos, procesos y buenas prácticas.

• Gather business requirements • Analyze source systems • Define underlying data sources and transformation requirements • Design data models • Develop metadata for data analysis and visualization • Collaborate with business areas and project teams • Elicit, identify, prioritize, and document data visualization and business intelligence requirements • Serve as a functional and technical data visualization expert • Translate business analysis into prototypes concepts of reports and dashboards • Document data acquisition, data management, and data governance processes • Implement process improvements and efficiencies • Create training materials and user guides • Conduct training sessions with end users

• As a key team member, You would be responsible for collecting, transforming and validating the data required for MMM Models. • Using Advanced Excel & Python, you would be required to manipulate and transform the raw data into model ready datsets. • The processed data needs to be warehoused in Azure and presented using PowerBI. • You would have to validate and derive insights from the transformed data to assist modeling team in building hypotheses for the MMM Models. • This will be for various datasets – Consumption or POS data, Media – both online and offline, Medical Expert & Finance data • You will be seen as a strong voice of influence for sharing ideas and contributing to innovation of the entire data ingestion process from source to modeling