Vibudh Singh
Lead Machine Learning Engineer at S&P Dow Jones Indices
Vancouver, British Columbia, Canada
Summary
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Senior🎓
Top SchoolVibudh Singh is a Lead Machine Learning Engineer with 8 years of experience building and productionizing ML solutions across finance, energy regulation, and operations research. At S&P Dow Jones Indices he designs and deploys LLM- and NLP-driven systems to surface emerging industry trends and power a company-comparison chatbot. His background blends deep learning (BERT, CNNs, Transformers) with practical MLOps on AWS/Azure/GCP, honed while scaling prototypes into public-facing services at the Canada Energy Regulator. Earlier roles in analytics and revenue optimization demonstrate a strong applied-statistics and business-first mindset, able to translate model outputs into measurable commercial impact. Based in Vancouver, he pairs an electrical engineering foundation with an MBAN from UBC Sauder, making him comfortable at the intersection of rigorous modelling and stakeholder-facing product work. Colleagues describe him as the kind of engineer who moves quickly from research prototypes to robust, auditable production pipelines.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Technology (B.Tech.), Electrical Engineering, Bachelor of Technology (B.Tech.), Electrical Engineering at Motilal Nehru National Institute Of TechnologyMaster of Business Analytics (MBAN), Business Analytics, Master of Business Analytics (MBAN), Business Analytics at UBC Sauder School of Business
Stackoverflow
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Github Skills (12)
des7
environmental7
extraction6
data-extraction5
python4
data-science2
machine-learning2
algorithms1
resume1
artificial-intelligence1
deep-learning1
ai1
Programming languages (3)
Github contributions (5)
iVibudh/TensorFlow-for-DeepLearning
Mar 2022 - Sep 2024
TensorFlow for Deep Learning
Contributions:11 reviews, 48 PRs, 226 pushes in 2 years 5 months
iVibudh/BAIT-509---Machine-Learning-
Feb 2018 - Apr 2022
Contributions:16 pushes, 1 branch in 4 years 1 month
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