Data Scientist

We are seeking a highly skilled Data Scientist to design and implement predictive models using high-dimensional, real-time datasets. The ideal candidate will apply advanced machine learning and data mining techniques to detect fraud and abuse, support strategic decision-making, and contribute to innovation through research and patent filings. This role requires strong technical expertise, storytelling with data, and experience in production environments. Key Responsibilities Design, build, and deploy predictive models for fraud and abuse detection, including account takeover (ATO), membership fraud, trial abuse, LTO abuse, and bot attacks. Own fraud/abuse risks for specific products or segments and act as a strategic partner to product development teams. Communicate insights and recommendations effectively through data storytelling and visualization. Build interactive dashboards and visualizations for internal and external stakeholders. Apply ML/AI, deep learning, and data mining techniques to develop robust anomaly detection models. Contribute to research initiatives and US patent filings to address emerging fraud issues and automate processes. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. Strong technical expertise in machine learning, statistical analysis, and data storytelling. Proficiency in Python and machine learning/data mining packages. Experience working with large datasets and distributed computing tools (GCP/BigQuery preferred). Experience with production deployment of models. Familiarity with GenAI and Agentic AI technologies. Preferred Qualifications Experience in fraud detection or anomaly detection domains. Knowledge of cloud-native tools and services for scalable model deployment. Experience in patent filing or research-driven innovation. #J-18808-Ljbffr Compunnel