Qingxia “Quency” Yu

646-***-**** ● adbqav@r.postjobfree.com ● www.linkedin.com/in/quencyyu ● www.qingxiayu.tech EDUCATION

University of Maryland, Robert H. Smith School of Business College Park, MD, USA MS in Information System (STEM), GPA 3.5 2019/12

University of California, Irvine, the Paul Merage Business School Irvine, CA, USA Bachelor of Arts, Business Administration, GPA 3.6 2015/09 SKILLS

● Programming: Python(numpy, pandas, scikit-learn, beautifusoup, scrapy), R, SQL, Scala

● Big Data: Spark, Hadoop, Pig, MapReduce, Hive

● Cloud: AWS (SageMaker, EMR, S3, Lambda, Glue)

● Certificate: AWS Certified Cloud Practitioner

● Machine Learning: Linear/Logistic Regression,

Random Forest, XG-boost, Ensemble Method

● Deep Learning: Tensorflow, Keras, CNN, GAN

● Visualization: AWS QuickSight, Tableau, Zeppelin

● Web: JavaScript, HTML, CSS, Django, Bootstrap

Work Experience

Data Scientist Intern, iSolvers 2019/05-2019/12

● Converted R code to Python and built various models in AWS SageMaker and EMR platform using Apache Spark

● Performed ETL by successfully transferring 100G+ data from Microsoft SQL Server to AWS S3 and Redshift using AWS Glue and built Data Lake in AWS

● Prepared project deliverables and documentation as needed to support Architecture-related processes such as the Cluster launch in EMR, Dockerfile to launch machine learning models and create UI interface Research Assistant, University of Maryland, Robert H. Smith School of Business 2019/08-2019/12

● Successfully scraped data from websites using python scrapy module and xpath

● Built pipelines to clean large dataset, constructed spark models and visualized the results using AWS Zeppelin Business Analyst, Goto Fufillment Services 2015/9-2017/10

● Monitored, analyzed and identified gaps in digital and social media presence using Google Analytics

● Built models using python to predict future products’ sales to assist product team make purchase decisions

● Composed analysis of strategies in team of six members, presented recommendations to form strategic partnerships and increase market share by 10%

● Collaborated with product teams manage advertising campaigns and optimized social media channel communication to align with advertising campaign increasing revenues by 15% and number of consumers by 40% PROJECTS

Market Regime Prediction with Text Features for Principal Financial Group 2019/8-2019/12

● Extracted, clustered and interpreted GB level text features datasets from S3 buckets using python, performed data cleaning, developing machine learning models to map text features signals into regimes to track market return and indicators for regime transitions

Python and Django Full Stack Web Development 2019/08

● Composed python/django code, css, HTML to launch a web application where users can log in and out, post blogs, and publish comments with vivid visualization webpage NBA Championship Prediction 2019/04

● Scraped data from website and cleaned data using Python beautifulsoup, requests, xpath

● Built models to predict teams who entered Playoff with accuracy of 93% and simulated upcoming competition results to predict final championship

Hospital Performance Evaluation 2019/04

● Collected, cleaned, and restricted the raw data to fit for different requirements of various machine learning models including XG-boost, random forest, lda, and regression, linear

● Set paraments ranges to predicted patients’ return to hospitals within three months to evaluate hospitals’ performance and the best model had 83% accuracy which rewarded second place in the competition Apartments Database Management 2019/03

● Wrote user stories, designed ER diagram and built a database in Microsoft Server SQL

● Analyzed data using advanced SQL queries to give renting suggestions to UMD students and received positive feedback from students

LEADERSHIP EXPERIENCE

Qingguo Education Center, Co-founder 2017/11-2018/07

● Developed a Mistake Collection Method on Math and Physics, enhancing class test results by 14%

● Performed customer profiling, segmentation, and post-campaign analysis on local marketing campaign; presented data to support business decisions to increase revenue growth by 21%

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