Hariom Tatsat
Vice President, AI Quant at Barclays Investment Bank
New York, New York, United States
Summary
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Senior🎓
Top SchoolHariom Tatsat is a Vice President and AI Quant at Barclays Investment Bank with over a decade of experience building quantitative models, leading AI and generative-AI initiatives, and translating research into production-grade finance solutions. He holds a Master’s in Financial Engineering from UC Berkeley and blends deep derivatives and risk-pricing expertise from roles at Nomura, RBS, and FAB with modern ML practice. Author of "Machine Learning and Data Science Blueprints for Finance," he also maintains a practical open-source Jupyter notebook template for end-to-end ML workflows in finance, showing his emphasis on reproducible, production-ready modeling. As an advisor at Berkeley SkyDeck and ongoing technical reviewer, he bridges startup mentorship, publishing, and enterprise deployment. Known for turning complex hedging and credit models into scalable AI systems, he brings both hands-on coding and strategic leadership to quantitative teams.
10 years of coding experience
6 years of employment as a software developer
Master’s Degree Financial Engineering, Master’s Degree Financial Engineering at University of California, BerkeleyCFA Level 3 Candidate Finance General, CFA Level 3 Candidate Finance General at CFA Institute, USAFinancial Risk Manager (FRM) Financial Risk Management, Financial Risk Manager (FRM) Financial Risk Management at GARPB.Tech Industrial Engineering and Management, B.Tech Industrial Engineering and Management at Indian Institute of Technology, KharagpurCertificate in Quantitative Finance ( CQF ) Quantitative Finance, Certificate in Quantitative Finance ( CQF ) Quantitative Finance at Fitch, 7 City
German
Github Skills (9)
data-preprocessing10
jupyter-notebook10
eval10
machine-learning10
dataprep10
python10
evaluation10
data-analysis10
data-transformation9
Programming languages (2)
Github contributions (5)
tatsath/fin-ml
May 2020 - Jan 2023
This github repository of "Machine Learning and Data Science Blueprints for Finance". Please star.
Role in this project:
Data Scientist
Data ScientistContributions:150 commits, 96 pushes, 6 comments in 2 years 9 months
Contributions summary:Hariom created a comprehensive Jupyter Notebook template for classification machine learning problems, applicable for both classification and regression tasks. This template encompasses various stages of a machine learning project, including data preparation, exploratory data analysis, model evaluation, algorithm comparison, model tuning, and finalization. The template is designed to guide users through the entire process, showcasing techniques such as data transformation and algorithm tuning, covering both common and advanced machine learning methods, including deep learning models.
pythonsciencedata-sciencemachine-learning-bookmachine-learning
tatsath/PortfolioOptimization
Oct 2020 - Jun 2021
Contributions:117 commits, 98 pushes in 8 months
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