Jiakai Wu

Experienced Machine Learning engineer with a diverse background in constructing data-intensive applications and solving intricate architectural challenges across various industries. Skilled in developing predictive models, processing data, and implementing data mining algorithms. Possesses strong expertise in programming languages like Python, Java, and R, along with proficiency in SQL and Spark.

Capable of developing, testing, and deploying highly adaptive applications to convert business needs into substantial deliverables.

Machine Learning Engineer 

• Designed an anomaly detection approach using both ARIMA and LSTM models for network time series data, improving 80% accuracy in alert generation
• Utilized K-means model to calculate the expected range for discrete dataset, enabling effective monitoring and implementation on 75% of pipelines
• Developed a machine learning system to identify and classify user's normal behavior while detecting any abnormal behaviors
• Possessed proficiency in establishing data pipelines and utilizing Pytorch to train and deploy LSTM, GRU, and CNN models on Azure and AWS

University of California, Berkeley

Master of Science in Analytics

University of California, Davis

Bachelor of Science in Statistics with Data Science Minor: Technology Management

GPA: 3.956/4.0 (with honor)