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Data Analyst, Data Scientist

Boston, MA
May 15, 2020

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Chiung-Chih, Lin

781-***-**** 92 Hammond St. #4, Boston, MA 02120 EDUCATION

Northeastern University Boston, MA

Master of Data Analytics Engineering, GPA: 3.8 / 4.0 Sep 2018 – Apr 2020

• Relevant Coursework: Data Mining, Statistics, Machine Learning, Natural Language Processing National Taiwan Ocean University Keelung, Taiwan

Master of System Engineering and Naval Architecture, GPA: 4.0 / 4.0 Sep 2012 – Jun 2014 Bachelor of System Engineering and Naval Architecture, GPA: 3.6 / 4.0 Sep 2008 – Jun 2012

• Honors: Academic Achievement Award, Research Scholarship SKILL

Languages: R, Python, C++, C, SQL

Data Science: Database, Data Mining, Machine Learning, NLP, Data Visualization, Statistics Frameworks: TensorFlow, Scikit-learn, PyTorch, Gensim, APIs, SQLite, AllenNLP Applications: Tableau, Jupyter, MySQL Workbench


KKday Taipei, Taiwan

Data Analyst Sep 2019 – Dec 2019

• Conducted regression analysis of website traffic, advertisement exposure, and revenue to produce a performance prediction 8% more accurate than prior predictions

• Transformed data from Google Analytics API into an internal database in Python for analysis

• Developed a procedure that combined data from 4 servers to increase data usability and efficiency by 30% in SQL

Marketing Analyst Intern Jul 2019 – Aug 2019

• Improved data flow for 1 million members by designing data-flow diagram which improved our process around developing marketing strategies

• Used Tableau to track, analyze, and visualize data on weekly, monthly, and yearly basis

• Applied correlation methods to internal customer data and behavioral data to predict and identify new potential products for target customers

Lite-On Taipei, Taiwan

Project Manager Dec 2017 – Aug 2018

• Managed 12 projects for web service companies (AWS, Facebook) and the relative ODM.

• Coordinated 4 teams of 20 engineers allocating resources and ensuring on time completion for 12 projects


Natural Language Processing ( Python )

• Implemented NLP fundamental topics with real-word data and evaluated the trained model

• Topics: Sentiment Classification, Language Identifier, Surname Generation, Viterbi Decoder for NER model, Cross-Language Word Embedding

Instacart – Customer Behavior Analysis ( R )

• Purpose: Predicts whether a product purchased by a customer will appear in their next order

• Techniques: KNN, Logistic Regression, SVM, Neural Network

• Results: Achieved the hightest 65% of accuracy based on training 100,000 records with Neural Network

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