Qualifications: 7+ years of experience as a Data Scientist, with a proven track record of applying advanced statistical and machine learning methods on real-world problems (or 3+ years with a PhD). Strong background and practical experience leading the end-to-end execution of complex Machine Learning projects. Comfort with the realities of risk modeling: highly imbalanced and adversarial data, delayed/noisy labels, and the precision-vs-recall tradeoffs of acting on legitimate users. Full ownership of projects from initial idea through production deployment, working closely with engineering to get there. Experience in Generative AI, defining, building and evaluating AI-agents and leveraging foundational language models for introducing advanced new capabilities within existing products and systems. Experience in working with large-scale data processing pipelines, Cloud Computing and Machine Learning Operations. Demonstrated habit of working with AI: actively use LLMs/agentic tooling in your day-to-day workflow, and you instinctively turn recurring problems into reusable automation. B.Sc in Computer Science, Software Engineering, Mathematics, Electrical, Statistics, or a related quantitative field.
