Data Analyst

EveryMatrix is a leading B2B SaaS provider delivering iGaming software, content and services. We provide casino, sports betting, platform and payments, and affiliate management to 300 customers worldwide.

But that's not all! We're not just about numbers, we're about people. With a team of over 1400 passionate individuals spread across twelve countries in Europe and Asia, we're all united by our love for innovation and teamwork.

Join us on this exciting journey as we continue to redefine the iGaming landscape, one groundbreaking solution at a time.

We are looking for a dedicated Data Analyst to join our team in London!

About the job:

This is a rare opportunity to shape how data-driven decision-making works at scale across an iGaming CRM platform — both from the inside and for the operators who rely on it. As Data Analyst, you will sit at the intersection of product and commercial impact. You will define what “good” looks like for player engagement, build the analytical foundations that power our CRM platform’s insight layer, and work directly with operators to translate raw data into strategies that grow retention, lifetime value, and campaign performance. You will not just report on what happened - you will define what should be measured, why it matters, and how to act on it. This role is as much about influence and expertise as it is about analysis.

What you'll get to do:

• Define the KPIs, metrics, and analytical frameworks that underpin our CRM platform’s reporting and intelligence capabilities.
• Work closely with Product and Engineering to shape what data gets captured, how it is structured, and how it surfaces to end users.
• Build and maintain dashboards, reports, and self‑serve analytical tools that operators can act on directly.
• Identify gaps in current data coverage and lead initiatives to close them.
• Partner with operators to understand their retention and engagement challenges, and translate those into data‑driven recommendations.
• Develop scalable insight frameworks - benchmarks, cohort analyses, segment performance models - that can be applied across multiple operators simultaneously.
• Produce regular insight packages that help operators understand player behaviour, campaign effectiveness, and growth opportunities.
• Identify cross‑operator patterns and trends that can inform product development and best practice guides.
• Analyse campaign performance across the full lifecycle: targeting, delivery, engagement, conversion, and retention impact.
• Define and evolve segmentation logic, player scoring models, and lifecycle stage definitions.
• Establish A/B testing standards and support teams in designing, running, and interpreting experiments.
• Build predictive indicators for churn, reactivation potential, and player value to support proactive campaign strategies.
• Act as the analytical authority in cross‑functional discussions with Product, Commercial, and Customer Success teams.
• Present findings and recommendations clearly to both technical and non‑technical audiences, including operator‑side stakeholders.
• Contribute to roadmap planning by surfacing data‑backed opportunities and gaps.

What we’re looking for:

• 5+ years of experience in a Data Analyst or similar role.
• Hands‑on iGaming CRM experience is essential – you must have worked within an iGaming operator or platform environment, with a strong understanding of player behaviour, bonus mechanics, and retention marketing.
• Deep understanding of CRM operations: campaign logic, segmentation, lifecycle marketing, and retention mechanics.
• Strong SQL proficiency – you are comfortable building complex queries, data models, and analytical datasets from scratch.
• Experience working with large‑scale behavioural or transactional datasets.
• Proven ability to define metrics and measurement frameworks, not just report against existing ones.
• Experience building dashboards and self‑serve reporting tools (e.g. Looker, Tableau, Metabase, or similar).
• Comfortable working directly with external clients or operators, translating their business questions into analytical answers.
• Strong written and verbal communication skills – you can tell a clear story with data.

Desirable:

• Familiarity with A/B testing methodologies and experiment design.
• Exposure to predictive modelling or working alongside data scientists on applied ML use cases (churn, LTV, propensity).
• Experience with event‑driven or streaming data environments.
• Python or R for analytical scripting and automation.

Here’s what we offer:

• 25 days of annual leave, with 2 additional days added each year, up to 35 days by your fifth year.
• Hybrid work schedule after the first three months of employment, with up to 50 days of work from home per year.
• Monthly meal allowance.
• Gym allowance.
• Access to online learning platforms like Udemy for Business and LinkedIn Learning, and a budget for external training.
• Two Free Fridays each year, limited to one per quarter.
• 3 sick leave days per year, no doctor's note required.
• 52 weeks of paid maternity leave, with 21 weeks fully paid.
• 4 weeks of paternity leave, plus flexibility to work from home full‑time until your child is 13 weeks old.