Mohammad Meregan

Background

About Mohammad Meregan

I’m a Senior Data Scientist and Economist with 8+ years of experience applying machine learning, optimization, and causal inference to real-world business problems across insurance, healthcare, education, and finance. I specialize in building scalable, explainable, and production-ready systems that drive measurable outcomes—whether it's reducing fraud, improving pricing accuracy, or optimizing resource allocation. Recent AI-driven solutions include: Fraud detection engine using BERT, Graph Neural Networks, and XGBoost — reduced false positives by 12%, surfaced fraud rings LLM-powered claims intake assistant (Amazon Bedrock + LangChain) — cut manual effort by 18% RAG-based GenAI summarizer for compliance — automated clause extraction, reduced audit time by 40% Forecasting and pricing models (TFT, GARCH, SHAP) — improved quote accuracy and underwriting decisions Retention and LTV models using causal inference and GenAI embeddings — improved campaign ROI I also lead MLOps and experimentation efforts (CI/CD, SHAP, DiD), mentor junior data scientists, and collaborate closely with stakeholders to translate data into action. I'm especially interested in applying AI to domains like supply chain optimization, risk analytics, and intelligent automation. If you're building impactful data systems in these areas, let’s connect.