Rahul Agarwal
Senior ML Engineer at Roku Inc.
Stony Stratford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolRahul Agarwal is a Senior ML Engineer with 11 years of experience building production-grade machine learning systems across e-commerce, advertising, and supply chain domains, currently at Roku after leading ML teams at Meta. He has driven end-to-end ML initiatives—from data pipelines and time-series forecasting with XGBoost to CV-based quality inspection (with a filed patent) and NLP-driven customer recovery—combining hands-on modeling with product and cross-functional leadership. Known for shrinking big-data workflows from hours to minutes and mentoring junior engineers, he pairs engineering rigor with pragmatic delivery. An autodidact data scientist and amateur guitarist based in the UK, he also maintains a practical blog-focused repo showcasing applied time-series work, reflecting a bias toward reproducible, production-ready solutions.
11 years of coding experience
10 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)Master of Science - MS, Data Science, Master of Science - MS, Data Science at Higher School of Economics
Github Skills (7)
xgboost10
machine-learning10
time-series10
python10
data-science10
microblogging8
blogpost8
Programming languages (5)
Github contributions (5)
MLWhiz/data_science_blogs
Dec 2019 - Dec 2022
A repository to keep track of all the code that I end up writing for my blog posts.
Role in this project:
Data Scientist
Data ScientistContributions:33 commits, 53 pushes, 1 branch in 2 years 11 months
Contributions summary:Rahul's primary contribution revolves around adding and developing time series analysis capabilities within the repository, specifically leveraging XGBoost for forecasting. This is evident from the addition of a notebook titled "Time Series Using XGB.ipynb" which points to practical implementation of a machine learning model for time-series data. The user is focused on applying machine learning techniques like XGBoost to solve time series forecasting problems.
xgboostpythondatablog-poststime-series
MLWhiz/mlwhiz.github.io
Mar 2017 - Dec 2022
Contributions:396 commits, 655 pushes, 1 issue in 5 years 10 months
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