Yi Sheng Chan
Verified Expert in Engineering
Data Science and Machine Learning Developer
Yi is currently working at Apple as a software engineer, building a platform and framework for training machine learning models on hundreds of millions of Apple devices in a privacy-preserving way. He has designed and built scalable ML systems and data infrastructure in cloud environments since 2014, and his expertise spans DevOps, ML, data engineering, both batch and streaming, and back-end web services. Yi's strongest skill is Python, Java, Spark, and SQL, coupled with good ML knowledge.
Portfolio
Experience
Availability
Preferred Environment
Git, DataGrip, IntelliJ, PyCharm, Slack, Linux
The most amazing...
...project I've led, designed, and implemented was an end-to-end ML system that runs on production for a fintech company valued at a few billion dollars.
Work Experience
Senior Software Engineer
Apple
- Designed and maintained a critical client Python library for training ML models on a massive scale.
- Built secure data aggregation platform for massive-scale data aggregation.
- Migrated critical web services for federated learning to run on Docker and Kubernetes.
Senior Data Engineer
WorldRemit
- Built a scalable data infrastructure fully on AWS, including data pipelines, a data warehouse, a data lake, a supporting spiky usage pattern, monitoring and alerting, and data processing initiatives across batch and streaming datasets.
- Led, designed, and implemented an end-to-end machine learning system for internal use to optimize marketing efforts.
- Reduced the training time required for a machine learning model by 95%, from 20 hours to one.
- Created an exactly-once stream processing pipeline, enabling self-service push notifications for user-defined queries.
Machine Learning Engineer
Dressipi
- Optimized performance of a machine learning model training and evaluation process, reducing training time by 50%.
- Improved the CTR on a recommendation system by 20% by implementing production-level code.
- Provided architectural decision support by building proofs-of-concept and prototypes.
Data Engineer
Student.com
- Designed and implemented a production-level stream processing pipeline in Scala, Akka, and Spark Streaming.
- Implemented a real-time dashboard using Spark Streaming, Kafka, and server-sent events.
- Conducted ad hoc data analysis, defined metrics, and produced data visualizations on a monitoring dashboard.
Data Science Software Engineer
Etu Corporation
- Designed and implemented Lambda architecture for a machine learning system, reducing refresh time from three hours to three minutes.
- Initiated, researched, and built a data processing pipeline and NLP-based machine learning models to enhance the recommender system. This improved the CTR by 50%.
- Improved the CTR by 30% by designing and implementing a new architecture for ensemble machine learning models.
- Implemented and optimized a large-scale, production-level data pipeline with Spark.
Experience
Churn Prediction System
Fraud Detection System
Lambda Architecture on a Recommendation System
Skills
Languages
Python, SQL, Python 3, Java, Scala, Ruby
Frameworks
Apache Spark, Spark, Hadoop
Paradigms
Data Science, ETL
Platforms
Amazon Web Services (AWS), Apache Kafka, Docker, Linux, Kubernetes
Storage
Relational Databases, Redshift, Data Pipelines, NoSQL, PostgreSQL, Apache Hive
Other
Stream Processing, Machine Learning, Distributed Systems, Big Data, Data Engineering, Recommendation Systems, GraphDB, Amazon API Gateway, APIs, Deep Learning
Tools
Apache Airflow, Git, Amazon Elastic MapReduce (EMR), Amazon Athena
Libraries/APIs
TensorFlow, PyTorch
Education
Master of Science Degree in Finance
National Taiwan University - Taipei, Taiwan
Bachelor's Degree in International Business
National Cheng Chi University - Taipei, Taiwan
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