Data Analyst

• Mar 2021 - Present

Data Science Co-op

• Sep 2019 - Dec 2019

Objective: Using the anomaly detection method and unsupervised learning method to support exception focused review process. Extracted data from 254 Oracle databases using python generated SQL scripts and made the data infrastructure analytically friendly. Performed feature selection among 200 features and utilized IQR and Mahalanobis distance method to detect part of anomalous data. Run Auto-encoder and K-means method on every group and targeted out the outliers which have large reconstruction error and large cluster centroid distance, save the output and helped the company review by exception. Show less

Graduate Teaching Assistant in Machine Learning Course

• Sep 2019 - Dec 2019

Designed Machine Learning Homework(Linear Regression, Support Vector Machine, K Nearest Neighbour) and Assigned them to students. Completed MLP, CNN, RNN Kaggle dataset challenge and assigned them to students. Homework grading and held QA sessions. Designed Machine Learning Homework(Linear Regression, Support Vector Machine, K Nearest Neighbour) and Assigned them to students. Completed MLP, CNN, RNN Kaggle dataset challenge and assigned them to students. Homework grading and held QA sessions.

Data Analyst Intern

• Jun 2016 - Aug 2016

• Designed Java crawler and SQL trigger to extract user data from the Web blog in China. • Extracted data from MySQL DB and developed JSP on MyEclipse to display backend data. • Visualized the data with Echarts API and analyze the trend of certain popular searches. • Designed Java crawler and SQL trigger to extract user data from the Web blog in China. • Extracted data from MySQL DB and developed JSP on MyEclipse to display backend data. • Visualized the data with Echarts API and analyze the trend of certain popular searches.