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You will sit at the intersection of statistics, data science, and high-performance software engineering, working directly with Core Product Managers and engineering teams to turn complex financial data into proprietary algorithmic advantages.\nResponsibilities\nResearch, design, and prototype behavioral, risk, and toxicity-scoring models for client and partner-flow segmentation\nBuild backtesting and monitoring frameworks to validate models, signals, and hypotheses across data of varying granularity\nDetect early risk signals, anomalies, and regime shifts in market and client behavior, including probability of critical capital loss\nDevelop explainable risk signals and labels for the R&D team, and long-term client value/risk models with forecasting\nConduct research and hypothesis-testing on client economics, flow quality, and model performance\nRequirements\n3+ years of experience as a Data Scientist / Quantitative Researcher \nExceptional knowledge of probability theory, statistics, 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