Senior Machine Learning Data Scientist

Job Description: Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructureTranslate complex fraud patterns into well-framed ML solutions: defining what to model, what success looks like, and where ML adds value vs. simpler approachesDesign and maintain feature engineering pipelines for model developmentMonitor model quality in production, tracking performance over time, detecting data drift, and determining when to retrainPartner closely with leadership, go-to-market, fraud operations, product, and engineering teams to define and execute effective fraud strategiesChampion a culture of continuous learning, experimentation, and collaboration across the fraud and broader data science teamsRequirements: Hands-on, proactive, and analytical professionals who are passionate about using data to solve complex, real-world problemsBachelor's degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics or related field3+ years of work experience building and deploying machine learning systems into productionStrong proficiency in Python and SQLStrong understanding of ML fundamentals: model selection, evaluation methodology, feature engineering, and common failure modesHands-on experience with PyTorch, scikit-learn, and XGBoost (or similar gradient boosting frameworks)High attention to detail, strong intellectual curiosity, and a deep understanding of user behavior and fraud patternsEmpathetic, humble, and collaborative team playerCandidates must be located within the continental United StatesBenefits: Competitive salary based on experience, with full medical and dental & vision benefits.Stock in an early-stage startup growing quickly.Generous, flexible paid time off policy.401(k) with Financial Guidance from Morgan Stanley.