Shiyun Liu

Phone: 518-***-**** Email: adhvn6@r.postjobfree.com LinkedIn: https://www.linkedin.com/in/shiyun-liu/ SUMMARY

Master student who is actively seeking data analyst opportunities, with sufficient project experience in business intelligence, data visualization, and machine learning. Strong knowledge of statistics, data analytics, database management and solid technical skills in Python, SQL and Tableau. EDUCATION

Rensselaer Polytechnic Institute Aug. 2019 - Dec. 2020 Master of Science in Business Analytics GPA 4.0

Coursework: Introduction to Machine Learning, Advanced Data Resource Management, Statistics for Managerial Decision Making, Advanced Quantitative Methods for Business, Applied Analytics & Predictive Modeling, Information Systems for Management, Marketing Analytics, Internet Marketing Southwestern University of Finance and Economics Sep. 2013 - Jul. 2017 Bachelor of Science in Economics GPA 3.4

Berlin School of Economics and Law (Exchange Program in Business Administration) Oct. 2015 - Jul. 2016 PROJECTS

Apache Spark based Movie Recommendation System

• Applied ETL process to analyze 100K ratings of 9,000 movies by 600 users from MovieLens small dataset and conducted OLAP with Spark SQL

• Utilized Alternating Least Squares algorithm via Spark APIs and conducted grid search to tune hyperparameters with the lowest RMSE of 0.573 in training data and 0.877 overall using Spark Data Frame

• Predicted movie ratings, customized movie recommendations and discovered movie similarities E-commerce Financial Anomaly Detection and Risk Analytics

• Built machine learning models in Python to predict and prevent fraudulent transactions

• Performed Exploratory Data Analysis on 138K+ transactional data and preprocessed data by feature engineering and imbalanced labeled data handling by SMOTE

• Developed Logistic Regression, Random Forest and XGBoost models, found the optimal parameters and evaluated the model via 5-fold grid search cross-validation

• Selected the best model with the best recall score of 0.636 and designed an alert system to prevent fraudulent activities Customer Churn Prediction in Telecommunications Industry

• Developed algorithms for telecom vendors to predict 5,000 users’ churn probability via Python based on labeled data

• Preprocessed data by data cleaning, categorical feature transformation and standardization

• Trained supervised machine learning models, including Logistic Regression, Random Forest and KNN

• Evaluated model performance of classification using 5-fold stratified-cross-validation technique with the best precision score of 0.93 and figured out the top five important features that influenced customer behavior INTERN

Strategy and Operations Consultant Intern, Deloitte Consulting LLP, Beijing Office Aug. 2018 - Sep. 2018

• Participated in the Smart Shenzhen project and constructed blueprint of urban planning

• Collaborated with IT consultants on integrating diverse emerging strategic technologies such as AI, virtual reality, digital twin, blockchain and SaaS to support the infrastructure of a data-driven smart city

• Designed the assessment system of Smart City including redistricting qualitative and quantitative indicators and their corresponding measures

TECHNICAL STRENGTHS

Tools: Python(NumPy, pandas, scikit-learn), SQL Server(SSMS, SSDT, SSRS), Tableau, Spark, Excel, Google Analytics Machine Learning: Classical & Penalized Regression Methods, Tree-based Models, K-Nearest Neighbors, K-means Statistics Analysis: Hypothesis Testing, A/B Testing, Model Evaluation Database: ETL, Data Warehouse

Certification: Tableau Desktop Specialist, Tableau Certified Associate, Advanced Google Analytics