Head of Analytics

Head of Analytics — Global Multi-Product Broker

Limassol, Cyprus (or remote within UTC–1 to UTC+4) · Reports to CMO · Greenfield function build

The company has scaled across CFDs, crypto, prop trading, and prediction markets without end-to-end analytics — and the person who walks in now gets to define what data-driven decision-making means there, permanently.

Most analytics leadership roles hand you someone else's stack, someone else's definitions, and someone else's hiring mistakes. This one doesn't. The company has no existing analytics function, no inherited architecture, and no canonical data model. It also has no prior Head of Analytics, which means no prior culture to unpick, no legacy tooling to defend, and no one else's choices to work around. The architectural decisions made here — attribution model, data stack, canonical metric definitions, testing methodology — are not modifications to someone else's framework. They are the decisions.

The mandate starts with acquisition attribution. The CMO needs to answer, for any campaign across any channel, what it cost, what it produced, and what those traders did next. That foundation — unified tracking from first click to live trading activity, across paid search, paid social, affiliates, mobile, and partner codes — is the condition that makes everything else possible. From there: a single source of truth for business-critical metrics, real-time KPIs across every major product, and a hypothesis-testing framework that gets teams running experiments instead of debating whether to. Prediction markets are on the horizon; this person arrives at exactly the moment data moves from nice-to-have to genuine competitive advantage.

This is not a role for someone who needs a running start. The first months require building from zero — infrastructure, tooling, practices — in an organisation that has operated successfully without them. That sentence should produce recognition, not hesitation.

Why this beats the seat you're in now

• Blank page, real authority. Unilateral control over data definitions, roadmap prioritisation, and build sequencing. The CMO is the escalation point for cross-functional conflicts — not a co-decider on routine calls.
• Your name on the foundation. The stack, the canonical model, the attribution methodology, the team culture — all of it takes the shape you give it, and stays that way. No one who spent five years maintaining an inherited instance can tell this story.
• Performance upside tied to impact, not discretion. The bonus is structured as a share of the incremental value this function generates — not a manager's year-end judgment call.
• Team built your way. There is no inherited team to manage around. Embedded analysts exist and will be directed by this role; longer-term hiring is a blank page you fill with culture first.
• Inflection-point timing. New products, new markets — the window where data definitions and infrastructure choices become permanent is open right now, not in two years.
• Breadth that consulting can't give you. You design the architecture and then watch it run at scale, own the outcome, and make the hiring decisions. The exit story is yours.

This is for you if

• You have built multi-touch attribution across paid, organic, and partner channels in a fintech or fast-moving digital business — and you have made a contested attribution model stick with channel owners who didn't want it to.
• You have made a defensible architecture call from a blank page — not just inherited and maintained someone else's stack.
• You currently hold a senior analytics role at a CFD, crypto, or adjacent broker and you are waiting for a function-head opening that may not come, or may not come with real authority when it does.
• You are an analytics consultant who has built greenfield stacks for financial services clients and wants to own the outcome rather than hand it back at the end of the engagement.
• You have killed a test stakeholders wanted to call a win — because the numbers didn't support it — and made that call land without losing the room.
• The absence of infrastructure reads as opportunity, not obstacle.

Your first year

The first six months are infrastructure and attribution — event collection, warehousing, transformation, and visualisation layers selected and stood up; UUID tracking live across every marketing channel; data governance documented and adopted. Month six to nine is about the canonical data model: getting teams who currently run on different definitions of "Client" and "Trader" to agree on one, and building the pipeline that makes those definitions operational. By month twelve, every major product has real-time KPIs tied to business outcomes, the hypothesis-testing framework is running (not being debated), and marketing KPIs are in dashboards used weekly in actual decisions. Throughout: directing the work of embedded analysts across the org, raising the floor on what good looks like, and beginning to hire deliberately for the longer-term team.

The ask

What's the one architectural or attribution decision you've made from scratch that you're most proud of — and what would you do differently?