About this role
Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 25 million users choose Tabby to stay in control of their spending and make the most out of their money. The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 70,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $18 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region. Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $6,5 billion.
About the role
- As the Senior Marketing Analyst for CRM, you will be the single analytics owner of CRM - the person marketers come to as a partner.
- You will own how campaigns are measured, how the communication data is built and trusted, and how insights turn into decisions: what to stop, scale, or fix.
- You will work closely with CRM marketers, Product, and the data platform team.
- You define what data you need and accept its quality; you do not build the pipelines yourself.
- Be the analytics partner to CRM marketers and Product on every initiative.
- Work with them on how to improve results.
- Answer "how do we correctly measure CRM activity" questions: choosing the right measurement design for a campaign type (always-on journeys vs one-off blasts vs product launches), defining what "delivered" means per channel, and defending the methodology to stakeholders Explain the technical side in plain language: how an experiment works, what a holdout is for, why a number can or cannot be trusted, so marketers make decisions they actually understand Own how CRM performance is measured: control groups, holdouts, A/B tests Own the CRM analytics data in dbt on BigQuery: who gets which message, on which channel, for which product, and how often Be the customer of the data platform team: say what data you need from the CRM and attribution tools, agree on timelines, and sign off on quality.
- You own what the numbers mean; they build the pipelines.
- Build Tableau dashboards that earn their place: visualisations stakeholders can open to check a hypothesis, answer their own question, or spot an insight in minutes.
- Keep the self-serve AI analytics assistant up to date, so non-technical colleagues can get answers to simple questions and run their own ad-hoc analysis without waiting for an analyst Work with a data science team, ask the right questions about a recommendation or propensity model, spot when it is not doing its job, and drive the test that proves it