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Main Responsibilities:   Take ownership of the company’s SQL Server data infrastructure, including development and maintenance of ETL pipelines. Ensure seamless integration with key third-party platforms. Drive a major affiliate network consolidation initiative, ensuring accurate data migration and clean attribution of revenue across channels. Develop and maintain a suite of Power BI dashboards for daily, weekly, and monthly reporting across various departments. Lead affiliate network consolidation, ensuring data consistency and revenue reconciliation. Support cross-team analytics needs with clear, accurate reporting. Explore AI/ML opportunities to drive predictive and automated solutions.   Desired experience: iGaming experience. 5+ years of experience in data engineering, BI, or analytics. SQL Server, Python-based ETLs, and building dashboards in Power BI. Proven ability to work independently, manage projects, and act as the link between business teams and technical teams. A proactive mindset geared toward innovation, scalability, and data-driven strategy.

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.