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Job Title: Data Privacy Analyst Location: On-site – Limassol, Cyprus About the Role We are seeking a Data Privacy Analyst to join our Data Protection team in Limassol. Reporting to the Data Protection Officer, you will manage privacy compliance, support risk assessments, and help maintain a robust global data protection framework. Key Responsibilities Handle data subject requests (access, deletion, portability). Maintain records of processing activities and document data flows. Conduct privacy risk assessments, DPIAs, LIAs, and vendor reviews. Support privacy incident investigations and regulatory reporting. Collaborate with internal teams to embed privacy-by-design. Assist in policy drafting and regulatory readiness projects. Requirements 2–5 years of experience in privacy, compliance, or risk management. Strong knowledge of GDPR and international privacy laws (CCPA, LGPD, etc.). Experience with DSARs, DPIAs, and vendor assessments. Excellent analytical, legal, and communication skills. Certifications such as CIPP/E, CIPP/US, or CIPM are a plus. Experience in regulated or data-intensive industries is preferred. What We Offer Competitive salary and bonus opportunities Career growth and professional development Collaborative on-site work environment in Limassol

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My client is seeking an exceptional Senior Sportsbook Data Science Engineer to lead advanced modeling initiatives that power user profiling, risk control, and personalized gaming experiences across their rapidly expanding Sportsbook and iGaming ecosystem. This position is a senior, high-impact role offering full ownership of model strategy, hands-on development, and leadership of data science best practices. You will build and deploy machine learning models that directly influence product innovation, risk management, and operational effectiveness. Key Responsibilities Modeling Leadership & Roadmap Ownership Own the end-to-end modeling roadmap for Sportsbook and iGaming user profiling, ensuring full alignment with business priorities, compliance needs, and risk strategy. Architect scalable ML pipelines for feature engineering, model training, deployment, and monitoring in production environments. Develop robust user segmentation and classification frameworks based on behavioral, transactional, and betting activity signals. Translate model insights into actionable strategy recommendations for cross-functional teams including Product, Risk, Marketing, and Operations. Mentor and support junior data scientists/ML engineers, driving excellence in experimentation, deployment processes, and model governance. 1. User Risk Control & CCF Modeling Build predictive models for user risk control coefficients (CCF) using behavioral, financial, and wagering-related data features. Automate the assignment of CCF risk tiers and design differentiated risk-control strategies per user segment. Continuously track model performance, detect drift, and optimize outcomes to support safer gaming, regulatory compliance, and risk-aware decision making. 2. Betting & Gaming Behavior Prediction / Personalization Develop predictive models for user behavior, including betting propensity, churn risk, gameplay depth, and long-term value forecasting. Build recommendation systems to personalize game/bet suggestions, promotions, and product experiences across Sportsbook and iGaming channels. Optimize personalization frameworks to drive engagement, retention, and user lifetime value. Qualifications 5+ years of hands-on machine learning/modeling experience in the Sportsbook or iGaming industry, with a proven track record of delivering production ML solutions. Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or a related quantitative field. Expert proficiency in Python and SQL, including data wrangling, feature engineering, model building, and evaluation. Deep knowledge of ML methods for classification, scoring, segmentation, recommendations, and behavior prediction. Demonstrated experience deploying models into production, with strong understanding of monitoring, drift detection, and feedback loops. Excellent communication skills with the ability to convey complex modeling results to non-technical stakeholders.