Nicholas Romano
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolNicholas Romano is a Solutions Architect with nine years of experience translating advanced ML and AI research into production-ready, cloud-native systems. He has led AI initiatives at scale—most recently as VP Applied AI Lead at JPMorgan Chase—building models on one of the largest consumer data repositories to drive marketing, finance, and operations decisions. Nicholas’s background in structural engineering and computational research informs a pragmatic, measurement-driven approach: early in his career he automated bridge design and sped research discovery by 60% using Elasticsearch and Python. He is fluent across the ML stack (TensorFlow, PyTorch, PySpark) and cloud tooling (AWS, EKS, Lambda, Databricks), with hands-on expertise in Docker, Kubernetes, and MLOps orchestration. Known for clear communication to both technical and non-technical stakeholders, he consistently bridges research rigor with business impact. Based in New York, he focuses on deploying foundation-model and cloud-first solutions that scale enterprise decisioning.
9 years of coding experience
9 years of employment as a software developer
Architectural Engineering, Structural Concentration, 3.52, Architectural Engineering, Structural Concentration, 3.52 at Drexel UniversityMaster of Science - MS, Computer Science - Data Science Concentration, Master of Science - MS, Computer Science - Data Science Concentration at Rutgers University
Github Skills (9)
summaries10
flask8
python7
elasticsearch-client7
elasticsearch6
search-engine6
client-library6
collaboration6
elastic4
Programming languages (3)
Github contributions (5)
nromano7/strategic-research
Jun 2018 - Jun 2019
Strategic (Re)Search was developed to make undiscovered public knowledge discoverable. We designed this tool to process, analyze, and present research data from thousands of project proposals, summaries, and publications. The goals of this project are to give Research Program Managers the ability to search for potentially undiscovered research, identify subject matter experts, and to present the results in such a way that facilitates identification of potential gaps in research or opportunities for collaboration. Tools used: Elasticsearch, Flask, Python.
Contributions:94 commits, 2 PRs, 33 pushes in 1 year
pythonflaskabilitycollaborationfacilitates
nromano7/nromano7.github.io
May 2017 - Jan 2018
Contributions:2 PRs, 78 pushes, 7 branches in 8 months
reactnextjs
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