Summary
Muhammad Mahendra is a data scientist with eight years of experience and 3+ years focused on building production recommendation systems for large-scale e-commerce and short-video platforms. He has driven end-to-end ranking and personalization projects at Tokopedia and ByteDance, specializing in feature engineering, combined ranking frameworks (e.g., DIN, XDeepFM, surrogate income models) and integrating recommendation infrastructure across partners. Comfortable with the full ML stack on GCP (Python, C++, BigQuery, Vertex AI, Airflow) and cross-functional collaboration, he has delivered solutions spanning push-notification propensity, cross-selling, and gen-AI shopping assistants. His background blends academic AI research and practical time-series forecasting in a startup setting, and he brings an uncommon mix of deep algorithmic work and product-facing integration experience in APAC markets.
8 years of coding experience
9 years of employment as a software developer
Mahasiswa, Informatics, Mahasiswa, Informatics at Universitas Telkom