Applied Scientist, Trust & Safety

Expert knowledge of machine learning techniques, including classification, anomaly detection, and natural language processing (NLP). Ability to effectively read, write, and debug code in programming languages such as Python Good knowledge of probability and statistics, including experimental design, optimization, and causal inference Demonstrated ability to create and drive technical and impactful roadmaps for the business, and lead seamless execution Ability to break down complex problems rigorously and understand the tradeoffs necessary to deliver impactful projects Ability to communicate clearly and effectively to cross functional partners of various technical levels

Initiate and drive applied science initiatives Architect and deploy machine learning systems to production Design and execute experiments Analyze a wide variety of data Collaborate with engineering, product, and operations teams Maintain the right balance between speed of execution and scientific rigor when designing solutions Contribute to improving the overall performance of Trust & Safety models by exploring new features, algorithms, and data sources.