Stripe runs on data correctness more than almost any company in the world. My background — production data pipelines and full-stack apps feeding clinical reports at Tempus AI, where mistakes have direct patient consequences — is unusually well-suited to that bar.
Hand-picked because they map most directly to the work at Stripe.
Collection of algorithmic coding challenges solved in Python and C++, covering data structures, string manipulation, and SQL/Pandas data analysis across easy to hard difficulty levels.
End-to-end ML pipeline for security threat detection including data preprocessing, feature engineering, model training, and evaluation on real-world security datasets.
Hands-on security assessment identifying and exploiting API vulnerabilities including authentication bypasses, injection flaws, and authorization issues.
Network security simulation demonstrating BGP route hijacking attacks in Mininet, implementing multi-router topologies with Quagga/Zebra and real-time attack visualization.
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