Senior Data Analyst - AI Personalisation & Digital Growth

Senior Data Analyst - AI Personalisation & Digital Growth

Madrid / Malaga  Office - Hybrid: 4 days in the office, 1 day working from home

Why This Role Exists 🎯

Ebury has just launched a completely refreshed brand, visual identity, and re-platformed every client-facing system. Now we need to make this new identity convert. We need someone who can connect the dots between our data warehouse, our AI capabilities, and our digital channels to answer one fundamental question:

How do we turn every client touchpoint into a bespoke, high-converting experience — so each client feels like the only client?

Today, tracking critical product adoption and conversion metrics across channels requires manual SQL and reconciling inconsistent tracking tools. Tomorrow, we want a single source of truth — automated, reliable, and actionable — that not only reports on performance but actively drives personalisation across the website, app, emails, and every journey a client touches.

What You'll Own 📌

Digital Analytics & Conversion Intelligence

• Build and own the Unified Product Adoption & Marketing Analytics Framework — the single source of truth for client behaviour across Web, Mobile App, API, and offline channels.
• Track the full client lifecycle: from first website visit → onboarding → first transaction → expansion into new products.
• Identify conversion drop-offs by country, channel, and business line, and propose data-backed interventions.

AI-Driven Hyper-Personalisation

• Design the analytics and data foundations for hyper-personalised client experiences — leveraging the context built in our client intelligence graph to deliver bespoke interfaces, content, and product recommendations.
• Collaborate with the AI Platform team to define and measure personalisation experiments: what content, offers, and journeys should each client segment (or individual client) see?
• Work with the Growth and Marketing teams to connect personalisation signals to email campaigns, in-app nudges, and outbound sales enablement.

What You Bring 🛠️

Must-Have

• 5+ years in digital analytics, growth analytics, marketing analytics, or a related data-intensive role — ideally in fintech, e-commerce, or SaaS.
• Deep expertise in client journey mapping and funnel analytics across web and mobile platforms.
• Strong SQL skills and experience working with data warehouses (BigQuery, Snowflake, or similar) — you can go from raw backend data to insight without relying on front-end event tracking alone.
• Understanding of tracking and attribution: cookies, UTM parameters, identity resolution, cross-device tracking, and the limitations of third-party tools (GA, Segment, Statsig).
• Experience with experimentation frameworks (A/B testing, multivariate testing) — you know how to design, run, and interpret experiments at scale.
• Analytical mindset with the ability to translate data into commercial recommendations.

Highly Valued

• Experience building or contributing to personalisation systems — recommendation engines, dynamic content, propensity scoring, or similar AI-driven features.
• Familiarity with ML/AI concepts relevant to personalisation: collaborative filtering, NLP for content matching, customer lifetime value modelling, churn prediction.
• Experience with marketing automation platforms (Pardot, HubSpot, Braze, or similar) and understanding of how data feeds into campaign orchestration.
• Knowledge of dbt or similar transformation frameworks for building clean, tested, documented data models.
• Exposure to event-driven architectures and real-time data pipelines (Kafka, Pub/Sub).
• Experience in a regulated financial services environment (payments, FX, banking).

What We Offer 💎

• Competitive Salary + Performance-based discretionary bonus.
• Other Benefits: Private health insurance, flexible remuneration, and a day off on your birthday.
• Career Progression: A well-structured career path with clear opportunities for growth.
• Vibrant Culture: Join a collaborative environment in our new Madrid office where Data Engineers, Data Scientists, Analytics Engineers, and Analysts work as one.
• Continuous Learning: Personal development through certifications and specialized training.

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