Daniel Jacobs

WORK HISTORY

EDUCATION

SKILLS

ABOUT DANIEL JACOBS

I am a data scientist with experience delivering applied machine learning and NLP solutions for institutional investors, including pension funds, asset managers, and hedge funds. My focus is on building reproducible ML pipelines, designing LLM-based systems, and translating research into scalable business applications.At Sibli, I worked with top Canadian and U.S. investment managers to deliver NLP/LLM workflows for ESG feature extraction, multilingual report parsing, and regulatory monitoring. These projects resulted in multi-year contracts and integration of ESG and climate-impact insights into long-term investment signals.My background includes PhD research in biomedical engineering at the University of Toronto, where I developed published seizure prediction and localization systems using EEG and novel signal features TBME, JTEHM, Brain Communications).Core skills include:ML & NLP: Deep learning, transformers, LLM workflows, RAG, text embeddings, topic modellingTools: Python (PyTorch, scikit-learn), PostgreSQL, Bash, Git, Docker, cloud services (AWS, GCP, Azure)Collaboration: scoping statements of work, stakeholder engagement, technical documentationI bridge research and production, turning advanced ML methods into tools that support data-driven decision-making in high-stakes domains.