Remote Jobs.

My client is a leading crypto casino, sportsbook, and prediction markets platform. They are now expanding and seeking to collaborate with a Prediction Product Marketing Manager; a strategist who lives at the intersection of markets, marketing, and momentum. You will drive the go-to-market strategy, positioning, and performance of the company's prediction vertical, defining how it shows up in the market, how we tell the story, and how we turn global conversations into participation. If you understand prediction markets, trading culture, and crypto communities and can turn insight into traction, this collaboration is for you. Strategy & Proposition Development Develop and deliver the end-to-end marketing and proposition strategy for the company's new prediction vertical. Define value propositions and positioning across multiple market categories; sports, crypto, politics, and culture. Identify emerging trends within prediction markets, trading, and entertainment to inform commercial direction. Build business cases that connect user insight, opportunity, and brand positioning. Market & Customer Analysis Analyse audience behaviour, motivations, and trends to shape differentiated messaging. Monitor competitor activity to identify whitespace and edge opportunities. Go-to-Market & Lifecycle Management  Oversee launch and rollout of new features, markets, and verticals. Align campaign calendars with marketing, CRM, and community initiatives. Deliver structured creative briefs and ensure campaigns align with brand tone and positioning. Performance & Optimisation Track performance KPIs across user acquisition, engagement, and retention. Required Skills & Experience 5+ years of experience in product marketing, proposition management, or growth strategy within prediction markets, crypto trading, fintech, or sports betting. Proven experience launching and scaling digital or trading-related products. Strong commercial and analytical mindset, with the ability to link market insight to business performance. Crypto-native mindset: understanding of blockchain, tokenized economies, and Web3 behaviours. If you are excited by the idea of defining how a prediction vertical shows up in the world and how it wins, let’s talk. Apply Now directly or email me at: chrysavgi.patera@pentasia.com  

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.