Our client, a leading global online retailer, offers an extensive selection of products, spanning fashion, electronics, home essentials, books, and more. Recognised for its unwavering commitment to customer satisfaction, the company ensures seamless shopping experiences with fast, reliable delivery and easy returns. With a strong focus on innovation and a customer-centric approach, they continue to shape the future of digital commerce.
Job Description
Experimentation Strategy & Test Design
* Develop and lead a structured testing strategy for paid media, ensuring experiments provide insights into incrementality, efficiency, and channel optimisation .
* Design and implement causal inference methodologies, including A/B tests, holdouts, and time-based experiments across major platforms ( Google, Meta, TikTok, Programmatic, etc. ).
* Partner with Marketing Analytics and Data Science teams to integrate best practices in media measurement, attribution, and statistical modelling .
* Stay ahead of emerging trends in marketing measurement and experimentation, ensuring our testing framework evolves with industry advancements.
Data Analysis & Business Insights
* Analyse experiment results to determine statistical significance, incremental impact, and long-term value for brand awareness, consideration, and conversion outcomes .
* Develop frameworks for aggregating test results, benchmarking, and meta-analysis to drive strategic decision-making.
* Collaborate with marketing and media teams to translate test findings into actionable insights that optimise media spend and performance .
* Communicate data-driven recommendations to influence budget allocation and investment strategies .
Testing Roadmap & Knowledge Management
* Develop a prioritised testing roadmap, aligned with marketing objectives, budget cycles, and innovation needs.
* Maintain a centralised knowledge hub for past experiments, key learnings, and best practices, ensuring consistent methodologies across teams.
* Educate stakeholders on incrementality measurement, attribution models, and the difference between platform-reported results and true business impact .
Qualifications
* Expertise in marketing measurement and experimentation, with hands-on experience in incrementality testing, causal inference, and media analytics .
* 5+ years of experience in marketing analytics, media measurement, or data science, preferably within digital marketing, media agencies, or ad tech.
* Strong knowledge of A/B testing, Lift Studies, regression modelling, and advanced measurement techniques .
* Experience working with large-scale paid media data across performance and brand marketing campaigns .
* Proficiency in SQL, Python, R, or similar analytics tools (a strong plus).
* Excellent communication skills, with the ability to translate complex data into clear business recommendations for senior stakeholders.
Additional Information
⭐️ Benefits
* Flexible hybrid working model, allowing for 60% (or more) remote work each week, tailored by each team for optimal collaboration.
* Opportunity to work remotely from abroad for up to 30 working days each year.
* Starting with 27 vacation days per year.
* Available relocation assistance, subject to prior agreement.
* Access to family services, including counselling and support.
* A variety of health and wellbeing options, including access to Wellhub.
* Comprehensive mental health support and coaching.
Application Details
Start date: As of now
Working time: Full-time
Application documents: CV