Shamindra Shrotriya
Principal Data Scientist - Centroid Retail Intelligence
Sydney, New South Wales, Australia
Summary
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Senior🎓
Top SchoolShamindra Shrotriya is a Principal Data Scientist and AI solution architect based in Sydney with 11+ years of experience building production-ready analytics and forecasting systems across retail, banking, and healthcare. At Walmart he develops Bayesian dynamic linear models for flexible, high-accuracy demand forecasting, drawing on a strong foundation in statistics from UC Berkeley and a PhD in Statistics from Carnegie Mellon. He has led data science teams and infrastructure projects—designing ETL pipelines, A/B testing frameworks, and monitoring dashboards—to help organisations turn messy data into reliable decision drivers. As an academic instructor and co-director of a national diversity-focused summer program, he blends research-grade methods with practical teaching and mentorship. His open-source work includes contributing a Python implementation of iterative Random Forests, signaling a rare mix of deep theoretical expertise and hands-on ML engineering. Colleagues value him for translating complex nonparametric techniques into scalable business solutions that improve customer targeting and operational forecasting.
11 years of coding experience
9 years of employment as a software developer
Master of Arts - MA Statistics, Master of Arts - MA Statistics at University of California, BerkeleyBaulkham Hills High SchoolDoctor of Philosophy - PhD Statistics, Doctor of Philosophy - PhD Statistics at Carnegie Mellon UniversityUNSW Sydney
Github Skills (90)
applescript10
linear-regression10
linear-models10
defaults10
r-package10
dock10
macbook-pro10
touchbar10
r9
sampling9
distill9
statistics9
developer-tools9
density-estimation9
knitr9
Programming languages (14)
Github contributions (5)
shamindras/ss_dotfiles
Nov 2020 - Dec 2022
Contributions:1 PR, 59 pushes, 2 branches in 2 years 1 month
Yu-Group/scikit-learn-sandbox
Apr 2017 - Aug 2017
Contributions:66 PRs, 34 pushes, 1 branch in 4 months
pythondata-scienceiterativesandboxmachine-learning
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