Sean Kim
Senior Manager Lead Scientist, Ai Strategy & Enterprise Model Governance @Hyundai Capital America
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WORK HISTORY
Senior Manager Lead Scientist, Ai Strategy & Enterprise Model Governance @Hyundai Capital America
Irvine, CA, US
Enterprise-facing role leading experimentation, personalization, and model governance across Marketing, Risk, Product, and Credit. Partnered with product and engineering to scale experimentation infrastructure, align ML outputs with business metrics, and influence roadmap and investment decisions. Increased retention by 25% and ROAS by 18% through uplift models powering lifecycle campaigns Delivered 20% lift in conversion by embedding causal inference into pricing and promotion tests Built a GenAI-powered governance platform (LangChain + LLaMA3) that reduced model validation cycles by 25% Replaced 100+ manual rules with ML-based decisioning, improving funnel efficiency and driving $15M in annual revenue Presented monthly to Risk Control Committee to align experimentation insights with executive decisions Managed a team of 4 scientists (2 senior, 2 junior) and set standards for enterprise experimentation across teamsDetailed Skills: Product Experimentation, Lifecycle Analytics, Causal Inference, Monetization, AI Governance, Uplift Modeling, Executive Reporting, GenAI Tools, Python, SQL, LangChain, LLaMA3, SageMaker, SAS Viya, Test Velocity
EDUCATION
Carnegie Mellon University - Tepper School of Business
Master of Science - MS
Hanyang University
Bachelor of Engineering (BE)
ABOUT SEAN KIM
Lead Scientist specializing in product experimentation, monetization analytics, and lifecycle optimization across growth, credit, and platform products. I help product teams move faster by designing scalable experimentation systems, aligning model outputs with business strategy, and translating analytics into confident roadmap decisions.At Hyundai Capital America, I lead experimentation and product analytics across Marketing, Risk, and Product. I built uplift modeling pipelines that increased retention by 25% and ROAS by 18%, ran pricing experiments that lifted conversion 20%, and deployed ML-based decisioning systems that replaced 100+ manual rules, driving $15M in annual revenue uplift. I also built a GenAI-powered governance platform (LangChain + LLaMA3) that reduced model validation cycle time by 25% and became the standard for experimentation documentation.Previously, I led experimentation and predictive modeling at Hyundai Capital, transitioning legacy SAS to Python ML frameworks and reducing development cycles by 30%. I built simulation models to help executives allocate $50M+ in product investment by quantifying trade-offs between conversion and risk. My fraud detection models saved $6M annually while maintaining approval stability in high-risk segments.Earlier, I consulted for Deloitte and Samsung SDS, delivering analytics infrastructure, anomaly detection pipelines, and customer lifecycle experimentation across financial services and digital platforms. I’ve worked in highly regulated environments, scaled experimentation systems org-wide, and presented directly to C-level stakeholders to drive adoption and strategy.I’m looking to contribute to a product-led company where experimentation, monetization, and lifecycle analytics drive growth. My value lies in building the systems that make faster, more confident decisions possible, and aligning those decisions with revenue, retention, and scale.Expertise: Product Analytics, Experimentation Strategy, Causal Inference, Monetization Analytics, Growth Analytics, Lifecycle Measurement, A/B Testing, Uplift Modeling, Funnel Optimization, Pricing Strategy, SQL, Python, CausalML, CatBoost, XGBoost, LightGBM, LSTM, DNN, SHAP, GenAI Governance, LangChain, LLaMA3, ML Validation, Test Velocity, Executive Reporting, Roadmap Influence, Model-Driven Strategy, Credit Products, Risk Analytics, Fraud Detection, Simulation Modeling, SAS to Python Transition, ROI Optimization, Revenue Uplift, Stakeholder Alignment, Enterprise Analytics, Cross-Functional Collaboration
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