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Xinchao(Luke) Lu
xinchao0509@gmail.com|513-609-1733|https://www.linkedin.com/in/xinchao-lu/
Summary
 2 years’ experience in software engineering, data analysis, and data visualization. Proficient at object-oriented
programming, database managing ,and data cleansing. Good at communicating with clients and getting requests
 Skills: Python, Java, MySQL, JavaScript, Hadoop, Docker, Kubernetes, Tableau, Pyspark, Pentaho, Pandas, Microservices
 Proficient with Linux, Bash, Git, and familiar with LaTeX, MATLAB
Professional Experience
Data Analyst Intern June – October 2018
GDS-services Shanghai, China
 Identifying 10 products’ latent issues for increasing 50% product specification accuracy using statistical analysis with Python
 Involving in using data parsers with Python to improve the efficiency of extraction from 1-day to 30 minutes
 Doing data cleansing of all data files, visualizing those results and analyzing with outputs of data visualization
 Present analysis results in a report with an explanation of tables and figures to clients without a technical background
Data Analyst Intern December – February 2018
HAIWAN Entertainment LLC New York, USA
 Working with a team which aim to specify the target customers for different products by analyzing the behavior of
customers on the company’s website
 Manage survey data and create new surveys as needed. Develop reports from surveys to share actionable insights with staff
 Creating and managing the database, and ensure technical and functional designs meet business requirements
 Communicating with the client for any requests and distributing all requirements to every group member with discussing
Education
Miami University
Bachelor of Computer Science May 2019 Oxford, OH
Relevant Course: Data Science with Python(A), Database Management System(A), Object-Oriented Programming(A), Big Data
Modeling & Analytics, Stochastic Modeling, Machine Learning
Academic Projects
Boston Housing Analysis
 Performing linear regression of 508 Boston housing data with 15 features and predicting the targets with training data
 Using performance metrics for regression to evaluate the model’s performance since prices are continuous numerical
 Visualizing each feature against targets with Python’s pyplot function which makes the output easier to be analyzed
 Predicting Boston housing price with analysis of visualized data and determining the performance of models
Twitter Analysis
 Mining data of 36895 twitters from Twitter with Python and converting those data to JSON format for future analysis
 Getting the frequency, popularity ,and time-frequency of words and analyzing the popularity of paired words
 Visualizing all output of analysis for determining key features that influence the popularity and getting the result
New York Weather Analysis
 Analyzing vehicular incidents in New York City with 900000 records of weather from the City of New York’s data website
with Hadoop
 Generating the output for each vehicle indicates the total count per vehicle type whether the vehicle type was involved in
an incident
Senior Design Capstone Information System
 Building a web application shows over 200 students’ in Miami University senior design
 Using PHP, HTML to build front end, and JavaScript, Python for the backend
 Presenting the project to clients in senior design gallery and explaining technical details for clients

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Xinchao(Luke) Lu

  • 1. Xinchao(Luke) Lu xinchao0509@gmail.com|513-609-1733|https://www.linkedin.com/in/xinchao-lu/ Summary  2 years’ experience in software engineering, data analysis, and data visualization. Proficient at object-oriented programming, database managing ,and data cleansing. Good at communicating with clients and getting requests  Skills: Python, Java, MySQL, JavaScript, Hadoop, Docker, Kubernetes, Tableau, Pyspark, Pentaho, Pandas, Microservices  Proficient with Linux, Bash, Git, and familiar with LaTeX, MATLAB Professional Experience Data Analyst Intern June – October 2018 GDS-services Shanghai, China  Identifying 10 products’ latent issues for increasing 50% product specification accuracy using statistical analysis with Python  Involving in using data parsers with Python to improve the efficiency of extraction from 1-day to 30 minutes  Doing data cleansing of all data files, visualizing those results and analyzing with outputs of data visualization  Present analysis results in a report with an explanation of tables and figures to clients without a technical background Data Analyst Intern December – February 2018 HAIWAN Entertainment LLC New York, USA  Working with a team which aim to specify the target customers for different products by analyzing the behavior of customers on the company’s website  Manage survey data and create new surveys as needed. Develop reports from surveys to share actionable insights with staff  Creating and managing the database, and ensure technical and functional designs meet business requirements  Communicating with the client for any requests and distributing all requirements to every group member with discussing Education Miami University Bachelor of Computer Science May 2019 Oxford, OH Relevant Course: Data Science with Python(A), Database Management System(A), Object-Oriented Programming(A), Big Data Modeling & Analytics, Stochastic Modeling, Machine Learning Academic Projects Boston Housing Analysis  Performing linear regression of 508 Boston housing data with 15 features and predicting the targets with training data  Using performance metrics for regression to evaluate the model’s performance since prices are continuous numerical  Visualizing each feature against targets with Python’s pyplot function which makes the output easier to be analyzed  Predicting Boston housing price with analysis of visualized data and determining the performance of models Twitter Analysis  Mining data of 36895 twitters from Twitter with Python and converting those data to JSON format for future analysis  Getting the frequency, popularity ,and time-frequency of words and analyzing the popularity of paired words  Visualizing all output of analysis for determining key features that influence the popularity and getting the result New York Weather Analysis  Analyzing vehicular incidents in New York City with 900000 records of weather from the City of New York’s data website with Hadoop  Generating the output for each vehicle indicates the total count per vehicle type whether the vehicle type was involved in an incident Senior Design Capstone Information System  Building a web application shows over 200 students’ in Miami University senior design  Using PHP, HTML to build front end, and JavaScript, Python for the backend  Presenting the project to clients in senior design gallery and explaining technical details for clients