Nicholas Abad

Data Scientist @Fuchs & Eule

Berlin, DE

Developed an automated building energy modeling pipeline leveraging publicly available 3D data to predict building components (e.g, roofs, walls, windows), reducing manual 3D model creation time from 3–8 hours to 3-8 seconds- Integrated physics-based simulations via a kernel endpoint to estimate building energetic states and financial KPIs (e.g, renovation cost, amortization time, energy and CO₂ savings) eliminating the need for manual Excel post-processing- Delivered a scalable in-use product that streamlined analysts’ workflows, combined data science with energy simulation, and significantly accelerated energy efficiency assessments for building portfolios- Collaborate daily with energy consultants, analysts, and software engineers to align technical solutions with actual practical needs, ensuring the products I build deliver real workflow improvements and value

Bellarmine College Preparatory

High School Diploma, General Education

Harvard Business School Online

PH527x: Principles, Statistical and Computational Tools for Reproducible Data Science

Ruprecht-Karls-Universität Heidelberg / Heidelberg University

Doctor of Philosophy - PhD, Faculty of Engineering Sciences (Molecular Biotechnology)

Lancaster University

Master of Science - MS, Data Science with Specialism in Statistical Inference

University of San Francisco

Bachelor of Science - BS, Mathematics with Minor in Computer Science