Tong Ka (Nora)

Email: adgqa2@r.postjobfree.com TEL: 412-***-**** LinkedIn: www.linkedin.com/in/tong-ka

EDUCATION

University of Pittsburgh Pittsburgh, PA

Master of Science in Information Science Apr.2020

RELEVANT COURSES: Data Analytics, Database Management, Data Structure, Cloud Computing, Machine Learning, Web Technologies, Data Mining, Information Visualization, Intro Neural Network Shanghai University of Finance and Economics Shanghai, China Bachelor of Management in E-commerce Jun.2017

RELEVANT COURSES: Object-Oriented Program Design, Computer Network, Decision Support System, E-commerce System Planning, Discrete Mathematics, Information Management INTERNSHIP EXPERIENCE

Changing the Present Data Analyst Aug.2020 – Present New York, US

Developed 10 + flexible layout submission forms for users and organizations with JotForm and HTML

Increased 12% accuracy of data by testing and mocking up data from JotForm submission

Combined and cleaned data from 15 cohorts for validation, transformed 5.5 million data based on business requirement Tsinghua TongFang Co., Ltd Big Data Mining & Analysis Engineer Aug.2017 – Mar.2018 Beijing, China

HealthCare Platform Project – targeting to design an information quality management & evaluation system o Ingested clients’ data from mobile devices and electronic health records, transformed all incoming data into common formats and schemas with Python

o With SQL server, built databases to store clients’ data, normalized the SQL tables to optimize data correctness and performance o Utilized algorithm models to provide basic analysis for physiological data, built dashboards to visualize patients’ data and the analytics results

Financial Insurance Customers’ Claims Project – targeting to manage and classify customers’ claims o Designed a Multi-Class Classification Algorithm Model to identify the label type of 20,000+ claims among 10,000+ customers o Applied Natural Language Process (NLP) and Feature Engineering to design a Binary Classification Prediction Model to predict the approval probability of each claim

o Tuned hyperparameters of models with GridSearchCV, used evaluation metrics (Precision, Recall, F Beta Measure, Threshold Variation) to handle the imbalanced data

Agricultural Bank of China Data Analyst Feb.2017 – May.2017 Jilin, China

Maintained and organized databases of cooperative enterprises with SQL for information updating and business tracking

Visualized data of financial product sales in Excel, Python, and Tableau to assist decision-makers with making summary reports and sale strategies

Built algorithm models (Linear Regression, Logistic Regression, and Gradient Boosting models) in Python to assist the lending department with loan capacity evaluation reports

SELECTED PROJECTS

San Francisco Crime Analysis and Prediction Feb.2020 – May.2020

Extracted, cleaned and transformed over 20 million criminal data from SFPD Crime Incident Reporting system

Visualized the data in multidimensional aspects using pandas, numpy and pylab dictionaries in Python, mapped the locations of crimes in the dataset to a geographic map to detect the distribution of criminal numbers in each district

Implemented Linear Models, KNN and ensemble methods to predict the category of crime, tuned the hyperparameters of the algorithms with Bayesian optimization (final logarithmic loss score: 2.36524, 14% lower than original models) P2P Online Lending Company Load Default Prediction Oct.2019 – Dec.2019

Preprocessed multiple types of 6000+ users’ data with Python, detected outliers, created new features based on the statistical analysis

Built multiple supervised learning models (Gradient Boosting, Random Forest and Neural Network) for prediction, used ROC, confusion matrix and k-fold cross-validation to evaluate model performances

Optimized the stability and performance of models using ensemble and stacking methods, increased model accuracy by 0.01 and achieved 2.4% improvement of AUC (75.7%), and analyzed feature importance with SHAP Summary Plot Online Movie Booking Website Construction Oct.2018 – Dec.2018

Developed and deployed a fully functional e-commerce website allowing users to browse and book movie tickets, permitting the administrator to aggregate, analyze and visualize the data of booking movies with front-end library of jQuery and Bootstrap

Designed and implemented Back-end databases (including 7 entity sets with 50+ attributes) using MySQL, MongoDB, and open- source packages

Connected front-end and back-end by implementing asynchronous requests with Ajax technology SKILLS

Programming Skills: Python (pandas, numpy, pylab, sklearn, plotly, TensorFlow), Java, R, SQL, MATLAB, JavaScript, jQuery Tools: MySQL, SQL Server, MongoDB, Teradata, Jupyter notebook, Tableau, Excel, Hadoop, Spark, ArcGIS, SPSS

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