Jincheng Sun is a Senior Data Science Consultant with 7 years of experience building production-ready ML systems and data platforms in the financial and tech sectors across Greater Montreal. He blends hands-on MLOps engineering—rewriting exploratory notebooks into Azure ML training pipelines, model registry/versioning, blue-green releases, and monitoring—with data engineering expertise in Databricks, Delta Lake and DBT implementing Medallion and dimensional models. At EY he authored an MLflow-based utility library to accelerate experiment tracking, model packaging and deployment (Seldon/Kubernetes), and has delivered monitoring stacks with Prometheus/Grafana. His background includes research-driven internships applying GNNs and reinforcement learning for VM scheduling and time-series anomaly detection, giving him a rare mix of research rigor and production pragmatism. Fluent in Python and cloud-native tooling, he focuses on transforming prototype research into reliable, auditable ML products for regulated environments.
7 years of coding experience
3 years of employment as a software developer
Master of Applied Science, Electrical and Computer Engineering, Master of Applied Science, Electrical and Computer Engineering at 加拿大肯高迪亚大学
Bachelor's degree, The Internet of Things, Bachelor's degree, The Internet of Things at China University of Petroleum 中国石油大学(华东)
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