Niall Smith
Sustainable Finance Quantitative Researcher @Bloomberg
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WORK HISTORY
Sustainable Finance Quantitative Researcher @Bloomberg
London, GB
I design and deliver new methodological approaches to measuring sustainability, climate, and biodiversity risks across companies, countries, and securities. These quantitative signals are integrated into Bloomberg Terminal products and support portfolio construction, index design, and investor decision-making worldwide.Some of my research projects- Developed pipelines to clean and standardize corporate carbon targets, now available on Terminal (ESG NETZ )- Built carbon emissions projection models using disclosed targets and historical trend extrapolation, delivered via Terminal (ESG NETZ )- Created climate transition alignment metrics enabling investors to optimize portfolios against decarbonization goals- Applied unsupervised learning to corporate biodiversity data to inform a scoring taxonomy for impacts and dependencies on nature- Enhanced the sovereign climate transition score methodology, now available on Terminal (GOVS ).
EDUCATION
St. Gerards Secondary School, Bray
Leaving Certificate
University of Limerick
Master of Science - MS, Artificial Intelligence
Trinity College Dublin
Bachelor of Arts (B.A.), Earth Sciences
Vrije Universiteit Amsterdam (VU Amsterdam)
Master’s Degree, M.Sc. Environment and Resource Management
SKILLS
ABOUT NIALL SMITH
Sustainability and AI professional operating at the intersection of quantitative finance, risk management and environmental/social issues. Over a decade of experience in transforming unstructured data into decision-making tools and insights for both investors and corporates. Professional track record spanning ESG research, sustainable finance, supply chain management and geospatial risk analytics. Academic qualifications in geoscience, environmental economics & policy, and Artificial Intellgience. I pride myself on being a multidisciplinary systems thinker while also product-minded. I am passionate about buildings things, while building skills.Thematic interest areas include climate and biodiversity risk modelling, natural capital accounting, ESG investing, greenwashing detection, and supply chain resilience. Technical skills and areas of interest include machine learning, statistical and geospatial analysis, MLOps pipelines, predictive modelling, NLP, LLMs/RAG, and last but not least, data visualization.Always open to connecting with like-minded individuals and innovators working on the future of sustainable finance, climate/nature, and AI for impact.
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