A competent, committed and experienced fresh graduate in computer science with 3+ years of diverse experience in deploying, implementing, administering, and supporting multifarious technologies in the fast developing and complex business facilities. Expert in algorithms and data structure, had project experience using Python, SQL, HTML, CSS, Spark, Hadoop, Docker, Java, UNIX and Networking. Self-motivated and eager to gain more implementation hands on experience and core network experience. Proactive and task-oriented professional, with an intensive background in conceiving and developing unique initiatives to propel technology to the limit and optimize performance. Proven ability to lead and work with a team to successfully complete projects efficiently and provide timely and effective incident responses, meeting service level agreements. Capable of handling the most challenging networks and delivering results.
Major in Computer Information Systems and Supply Chain Management, pubulished two top tier academic papers:
Studied at EECS department for algorithms and database, studied at Haas School of Business for Marketing and Economics
Partifipated in Berkeley RPP Project for constomer psychology analysis on statistics and data analysis, reported to professors and world-level researchers.
Summer School cooperated with Chinese Government, scholarship from Israel Government. Visited beatiful sceneries at Isreal. Here are some of my advice for you if you would like to go there:
Built complex SQL models to analyze structured data; used pandas DataFrame to gain customer insights and decipher customer purchasing behavior.
Effectively increased customer service efficiency by over 10% through identifying most important features of service data to internally improve customer service SOP.
Evaluated web service efficiency through researching customer behavior for online purchasing and browsing; cut costs and drove the consumer experience significantly.
Designed ER Diagram and constructed demo web application for technology industry based on client demand using Spring MVC framework, Mongo DB, and Neo4j.
Orchestrated and researched using Bloomberg terminals to research and analyze business data changes applying time series models; applied quantitative methods to calculate and forecast future changes of product prices.
Designed and implemented data ETL pipeline to automate client business verification process by efficiently computing customer information accuracy with scraped open source information using Rabin-Karp algorithm and RESTful APIs.
Researched large scale data and developed a client classification framework using Gradient boosting with parameterized feature selection approaches which outperforms published SVM baseline.
Designed and implemented an intelligent recommendation and prediction system using MapReduce framework and RESTful APIs connected to IMDb.
Implemented item-based collaborative filtering algorithm to decrease similarity of movies in co-occurrence matrix.
Effectively improved work efficiency through using B+ trees and hash table as indexes to process data.