Analyst Intern Data

YUANQING XU

New York, NY,***** 646-***-**** ******@***.***

OBJECTIVE

Graduate student in Data Science with rich industry experience especially in database management, statistical analysis and modeling, visualization and A/B testing. Proficient in Python, R and SQL. Seeking full-time positions. EDUCATION

New York University, School of Professional Studies, New York, NY May 2023 Master of Science, Management and systems Overall GPA: 3.89/4.0 Coursework: Machine Learning, Data Mining and Data Warehousing, Database Design and Management Hong Kong Baptist University (UIC campus), Hong Kong May 2020 Bachelor of Business Administration, Finance, Overall GPA: 3.45/4.0, Dean’s Honor list SKILLS

Technical Skills: R, Python, SQL, Tableau, AWS, Google Cloud Platform, Oracle Database Statistics & Machine Learning: Regression and Classification, A/B Testing and Hypothesis Testing, Time Series Analysis, Random Forest, XGBoost, Logistic Regression, Neural Networks

PROFESSIONAL EXPERIENCE

TEN company, Data Analyst Intern, New York, NY Feb.2023 – April.2023

● Designed and developed an end-to-end Oracle database using ERD and SQL that enables efficient storage, and connected with Excel to simplify the data accessing, saving 20% time for the team.

● Analyzed and visualized website visits and customer data using Python and Tableau to provide recommendations to stakeholders to optimize marketing strategies and social media performance.

● Proposed hypothesis that highlighting product review increases customer conversion, designed and conducted A/B testing, and analyzed results using t-test. It showed a 10% increase in conversion rate and sales volume.

● Developed an ecommerce landing website using HTML and CSS. Bluecow Business Strategies, Data Analyst Intern, New York, NY Jun.2022 – Aug.2022

● Implemented web crawler in Python to collect data from primary or secondary resources.

● Processed and analyzed 10K+ data in Python using numpy, pandas and sklearn, including outlier detection, missing data imputation, feature standardization and seasonality decomposition.

● Developed regression models using XGBoost to predict the sales volume of local newspapers and journals, identified important features and offered insights to stakeholders to boost their revenue. The Blackstone Group, Junior Analyst Intern, Shanghai, China Oct. 2020 – Dec. 2020

● Developed valuation models to measure product performance, with features such as empirical return, risk factors and financial status. It is widely adopted across teams to standardize the evaluation process.

PROJECTS

New York Airbnb House Price Analysis Jan. 2022 – Mar.2022

● Collected and transformed dataset with 4k+ rows, and implemented EDA (exploratory data analysis) such as correlation analysis, abnormality detection and seasonality decomposition in Python.

● Extracted 20 features including categorical, numerical and time-series features, performed VIF to test the multicollinearity of features, assessed and eliminated irrelevant features using PCT method.

● Built linear regression with regularization and Random Forest model to predict house price, tuned hyper parameters using cross-validation, and evaluated models on test dataset based on RMSE and MAE. AI-Hub Research projects, The Best Research Team Leader Jul.2019 - Sep.2019

● Reconstructed an option pricing model with the combination of the B-S model, Monte Carlo simulation and neural networks algorithms through extensive data analytics and simulation

● Trained and tested empirical S&P 500 index quotes in last ten years to review the volatility and accuracy of prediction through machine learning, SVM, Decision Tree, Logistic regression models

Contact this candidate