New York, New York, United States
As a Machine Learning Engineer at JPMorgan Chase, I build scalable Al solutions that enhance financial analytics, detect fraud, and streamline data-driven decision-making.
• Designed and optimized ML models that improved financial prediction accuracy by 35%, driving smarter business insights.
• Developed LSTM-based fraud detection models with 98% accuracy, strengthening compliance and transaction security.
• Boosted model performance by 10% through
BERT fine-tuning and GAN-based data augmentation for text analytics.
• Built CNN-powered anomaly detection systems, cutting fraudulent activities by 38% and improving transaction monitoring efficiency.
• Engineered FastAPI-based inference pipelines and deployed models on AWS (EC2, Lambda, SageMaker) and Google Cloud, reducing time-to-market by 30%.
• Automated ML workflows and leveraged time-series forecasting to optimize staffing, reducing operational costs by 30%.