Head of Analytics - Global Multi-Product Broker

About the role

Job Description (JD) Job Title Head of Analytics - Global Multi-Product Broker Location Limassol, Cyprus (Hybrid) or Remote (UTC−1 to UTC+4) Reporting To Chief Marketing Officer (CMO) About the Role We are seeking an experienced Head of Analytics to establish and lead our analytics function from the ground up. This is a unique opportunity to define the company's data strategy, build the analytics architecture, and create the foundations for data-driven decision-making across a rapidly growing multi-product brokerage business. Operating across CFDs, cryptocurrency, proprietary trading, and prediction markets, the business has reached significant scale without a centralized analytics function. As the first Head of Analytics, you will have full ownership of building the data ecosystem, defining business metrics, implementing attribution models, and establishing analytics best practices that will shape the organization for years to come. Key Responsibilities Analytics Strategy & Leadership Build and lead the company's first centralized analytics function. Define the long-term analytics vision, roadmap, and operating model. Establish data governance standards, metric definitions, and reporting frameworks. Partner with executive leadership to enable data-driven strategic decisions. Direct and mentor embedded analysts across multiple business functions. Data Infrastructure & Architecture Design and implement the end-to-end analytics technology stack. Select and deploy data warehousing, transformation, visualization, and reporting solutions. Build scalable analytics infrastructure to support multiple financial products. Develop a canonical data model across the organization. Ensure data quality, consistency, accessibility, and governance. Marketing & Attribution Analytics Design and implement multi-touch attribution across: Paid Search Paid Social Affiliate Marketing Mobile Acquisition Partner Programs Build unified customer journey tracking from first interaction through trading activity. Deliver accurate ROI and customer acquisition insights across all marketing channels. Establish standardized marketing performance metrics. Business Intelligence & Performance Reporting Develop real-time executive dashboards and KPI reporting. Create a single source of truth for business-critical metrics. Build reporting frameworks across CFDs, Crypto, Prop Trading, and Prediction Markets. Translate complex analytical findings into actionable business recommendations. Experimentation & Decision Science Establish a company-wide hypothesis testing and experimentation framework. Design and evaluate A/B tests and controlled experiments. Ensure business decisions are supported by statistically sound analysis. Champion a culture of evidence-based decision making. Stakeholder Management Collaborate closely with Marketing, Product, Technology, Operations, and Commercial teams. Resolve cross-functional alignment on data definitions and reporting standards. Present analytical insights to senior leadership and executive stakeholders. Team Building Lead, coach, and develop embedded analysts. Design the future analytics team structure. Recruit and onboard analytics talent aligned with company culture and business goals. Key Deliverables (First 12 Months) Months 1-6 Build the analytics infrastructure and technology stack. Implement event tracking across all customer touchpoints. Deploy centralized data warehouse and transformation pipelines. Launch UUID-based attribution across all marketing channels. Establish data governance framework and documentation. Months 6-9 Develop and implement the organization's canonical data model. Standardize definitions for key business entities and KPIs. Align stakeholders around consistent business metrics. Months 9-12 Deliver real-time KPI dashboards across all business lines. Launch experimentation and hypothesis testing framework. Enable marketing and product teams to make data-driven decisions. Begin scaling the analytics organization through strategic hiring. Required Qualifications Bachelor's degree in Analytics, Data Science, Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field. Master's degree is advantageous. Experience Required Significant experience in Analytics, Business Intelligence, or Data Leadership roles. Experience building an analytics function from the ground up. Strong background in financial services, brokerage, fintech, cryptocurrency, trading platforms, or similar digital businesses. Demonstrated experience implementing multi-touch attribution models. Proven success designing analytics architecture and selecting technology stacks. Experience leading cross-functional analytics initiatives. Experience managing or mentoring analytics professionals. Technical Skills Data Warehousing ETL/ELT Architecture SQL Python or R Business Intelligence tools (Power BI, Tableau, Looker, etc.) Marketing Attribution Platforms Event Tracking Frameworks Data Modeling Dashboa

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