Hi! I’m a Senior Data Scientist and AI/ML Expert with 10+ years of experience at Morgan Stanley, developing and deploying machine learning and predictive models to drive business outcomes. I simplify complex concepts and use predictive analytics and deep learning to build ML solutions, ...more

Hi! I’m a Senior Data Scientist and AI/ML Expert with 10+ years of experience at Morgan Stanley, developing and deploying machine learning and predictive models to drive business outcomes. I simplify complex concepts and use predictive analytics and deep learning to build ML solutions, delivering actionable insights for strategic decision-making and operational efficiency. If you believe 360 reviews, word on me is that I understand users’ needs, follow through, and stay calm under pressure. 𝐒𝐤𝐢𝐥𝐥𝐬 & 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: • 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Gradient Boosting (XGBoost, LightGBM), Random Forests, Neural Networks, Model Explainability (SHAP), Recommender Systems, Reinforcement Learning (Q-Learning, Proximal Policy Optimization) • 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 & 𝐍𝐋𝐏: Foundation Models, Transformers, Self-Attention, Autoencoders, Topic and Sentiment Analysis • 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈: LLMs (BERT, GPT, LLaMA), GANs, Text-to-Image (DALL-E, CLIP), Retrieval-Augmented Generation (RAG) • 𝐂𝐚𝐮𝐬𝐚𝐥𝐢𝐭𝐲: A/B Testing, Statistical Analysis, RCTs, Natural Experiments, Double ML • 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬: Python, R, SQL (MySQL, PostgreSQL), Bash • 𝐏𝐲𝐭𝐡𝐨𝐧 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, Transformers (Hugging Face), LangChain, OpenAI API • 𝐂𝐥𝐨𝐮𝐝 & 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬: AWS (SageMaker, EC2, S3, Lambda, Glue), Azure, Airflow, Snowflake • 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 & 𝐕𝐞𝐫𝐬𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Docker, Kubernetes, Git, GitHub • 𝐃𝐚𝐭𝐚 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Excel, Tableau, ggplot2 𝐊𝐞𝐲 𝐀𝐜𝐜𝐨𝐦𝐩𝐥𝐢𝐬𝐡𝐦𝐞𝐧𝐭𝐬: • 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐋𝐞𝐧𝐝𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬: Developed a Python-based lending classifier with a 60x lift, doubling hit rates over prior model. • 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠: Built time-series models forecasting $24B/year revenue with 1% deviation, optimizing financial planning. • 𝐏𝐨𝐬𝐭-𝐌𝐞𝐫𝐠𝐞𝐫 𝐌𝐨𝐝𝐞𝐥 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Led E*TRADE model integration post-merger, cutting maintenance costs by 50%. • 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐯𝐞 𝐌𝐋 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: Created an ensemble learning framework that reduced compute time by 80%, optimizing resources. • 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 𝐄𝐧𝐠𝐢𝐧𝐞: Designed a scalable macroeconomic forecasting engine, increasing model capacity by 35x for risk analysis. I’m completing my second doctorate in Electrical Engineering, focused on generalization in neural networks. I love communicating and using data to deliver solutions to critical business problems. Let’s connect!less