Data Analyst

CAN CHENG

Data Analyst / Business Analyst

TECHNICAL SKILLS

• Advanced MS Excel (5 years)

Pivot Table, Macro, VLOOKUP, Text Function

• SQL (2 years)

PostgreSQL, MySQL, SQL Sever

• Tableau/Power BI (2 years)

Visualizations, Reports, Dashboards, DAX

• Cosmos DB

• Azure

• Python (2 years)

Pandas, NumPy, Matplotlib, XGBoost, Seaborn

• Machine Learning (2 years)

Logistic regression, Neural Network, SVM

• Git • C# • SSRS / Kusto

PROJECTS

Zillow Real-estate Exploratory Data Analysis Python, EDA, XGBoost, time series

• Used missingno to explore and visualize the missing value and trained gradient boosting models with XGBoost to identify top correlated variables

• Explored variables with multicollinearity analysis and univariate analysis, visualize correlation among variables and training log error cost Text Classification with CNN Python, Jupyter Notebook, PyTorch, TorchText, Power BI

• Used TorchText to preprocess the text and transform it into GloVe vectors

• Implemented TextCNN and trained with PyTorch on a 10K records to identify whether the receipt item is preventive and achieved 0.98 accuracy Visualization for Movie Data SQL, EDA, PostgreSQL

• Wrote SQL query to generate movie data distribution that shows top popular movies

• Created dashboard to display movie's popularity, revenue and average vote according by different movie genre and illustrate the development of movie Hand-Written Digits Image Classifier Python, Jupyter Notebook, MLP

• Developed logistic regression model, multi-layer perceptron neural network.

• Manually implemented cross-entropy and back-propagation using NumPy. Sentiment Analysis C#, ML.NET

• Transformed text comments into tensor with TextFeaturizer

• Trained with FastTree model. Developed a console app that can detect toxic comments CERTIFICATES

Data Analyst Program Udacity 2018

• Data wrangling, exploring, communicating, and analyzing

• Applied inferential statistics and probability to real-world scenarios, built learning models and performed A/B tests. Machine Learning Stanford University, Coursera 2018

• Supervised learning (parametric/nonparametric algorithms, SVM, neural networks).

• Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). WORK EXPERIENCE

University Lecturer 01/2015 – 03/2018

Southwest Jiaotong University

• Excel for Analysis: Taught stock market analysis with advanced Excel, including SUMIF, VLOOKUP, Macro, Pivot Table, text functions, data visualization, and logical functions.

• Finance and Economics Background: Taught various curriculums in finance and economics areas, including microeconomics, macroeconomics, accounting, banking and investment.

• Mentorship: Mentored 15 students in thesis writing for every year, helping with subject selection and information collection. Managed the schedule of their progress. EDUCATION

Master of Science in Economics 09/2013 – 01/2015

University of Exeter, The United Kingdom

• Built econometric models: multi-linear regression, time series, regression, and panel data regression.

• Studied and analyzed economic activities in both macro and micro perspectives. Bachelor of Science in Finance 09/2009 – 07/2013

Southwest University of Nationality

• GPA 3.8; Song Qinling Scholarship; University Scholarship Tel: +425*******

Location: Kirkland, WA

Email: *****************@*****.***

LinkedIn: https://www.linkedin.com/in/can-cheng-047a2a133/

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