Shaurya Uppal is a data scientist with 9 years of experience building end-to-end ML solutions across FinTech, Retail, Adtech, Entertainment and RideHailing, most recently leading data science at Makro where he applied LLMs for customer life-stage segmentation and graph neural nets for recommendations. He has a strong track record of product impact—driving double-digit improvements in conversion, CTR and LTV through personalization, ranking and ad-targeting systems at InMobi, 1mg and epiFi—and holds a patent application on ads personalization. Comfortable from research to production, he has designed MLOps pipelines, worked with SparkSQL/Snowflake, DVC, BentoML and Airflow, and contributes to open-source data science tooling. Shaurya also mentors and creates educational content (ProjectPro courses, InterviewBit problem sets), reflecting an ability to communicate complex ideas clearly. He pairs a rigorous academic background (Georgia Tech MS, BTech with honors) with hands-on startup experience as an early hire, making him adept at building solutions from scratch under product constraints. An interesting facet: he blends classical ML (LightGBM, XGBoost) with modern NLP/LLM and graph approaches to solve diverse business problems end-to-end.
9 years of coding experience
7 years of employment as a software developer
HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, 12th: 94% | 10th: 9.8 CGPA, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, 12th: 94% | 10th: 9.8 CGPA at Mount Carmel School, Anand Niketan
Master's degree, Computer Science, 4/4, Master's degree, Computer Science, 4/4 at Georgia Institute of Technology
Bachelor of Technology - BTech (Honours), Computer Science, 8.6 (B.Tech with Honours), Bachelor of Technology - BTech (Honours), Computer Science, 8.6 (B.Tech with Honours) at Jaypee Institute Of Information Technology
Contributions:6 commits, 3 PRs, 5 pushes in 1 year 1 month
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