Waltham, MA
781-249-8512
juandu1124@brandeis.edu

Master of Science in Business Analytics - Academic Excellence Award
GPA: 4.0/4.0

Bachelor of Management in Logistics Management - Excellent Graduate
GPA: 4.3/5.0

Exchanging Program - First-Class Honours

Work Experience

Brandeis International Business School

Graduate Teaching Assistant 08/2022 - 12/2022

• Designed in-class exercises, checked assignments, proctored tests, and provided feedback and personalized guidance.
• Mentored students through office hours and one-on-one communication.
• Taught small groups of students focused on understanding the course material and working on complex SQL queries.
• Documented attendance and completed assignments to maintain full class and student records using Excel.

State Street Global Advisor (Brandeis Field Project)

Quantitative Researcher 06/2022 - 08/2022

• Analyzed the rolling correlation between each pair of stock indexes, created data visualizations using Python, and conducted research to provide explanations and insights.
• Built univariate and multivariate rolling regression models with and without regularization to predict sector return and tested two different time lengths used for forecasting.
• Constructed 1-month and 3-month portfolios using three weighting schemes and created python functions to backtest the portfolio performance using multiple measurements.
• Manually built classification tree algorithm to predict sector return movement and to proposed innovative solutions to incorporate the Gini impurity into portfolio construction.
• Facilitated weekly team meetings and delivered progress report to the senior members for review and discussion.

Urban Railway Company of CREC Electrification Bureau Group

Assistant to the Minister of Material and Equipment 06/2018 - 08/2018

• Categorized relevant information, including financial condition, past performance, delivery date and lead time of each supplier using Excel.
• Wrote competitive negotiation document based on negotiation invitation and instruction to bidders.
• Classified and filed relative material according to the negotiation document.
• Issued production and delivery plan to suppliers; monitored storage inspection process based on the material requisition plan of each department.

Academic Projects

Investigation on Brand rejuvenation of an old-honored brand, case study of Beijing Dao Xiang Cun Beijing, China

Team leader 04/2018 - 05/2018

• Guided through the process and set deadline for each intermediate objective.
• Designed questionnaires and interview outline; managed field research to identify current problems of company in relation to brand aging with team of three.
• Created a mind map to integrate four innovative methods and calculated a general budget for improvement measures.
• Presenting improvement approaches to help the company attracting younger customers and further developing potential market.
• Wrote a 15-page report to and delivered PowerPoint presentation to the company representative.

Investigations of Urban Fire Risk and Fire Protection Ability Beijing, China

Team leader 08/2017 - 09/2017

• Prepared a research plan and organized group meetings to decide on the best option.
• Applied stratified sampling to determine required sample size at each part, distributed 200+ copies of questionnaires.
• Filtrated available sample based on testing question set in the questionnaire, and utilized diagrams and imagery to present data.
• Drafted explanatory description of the risk level and the current protection ability and put forward plausible solutions to improve urban fire-fighting ability in the final report.

Case Study of Post-Merger Performance between Disney and Pixar Cork, Ireland

• Studied company's annual reports, presented data visualizations of the key metrics used in analyzing the merger reasons and assessing performance.
• Summarized four merging reasons, including technical requirement, competition pressure, human resource increment, and additional profits generated.
• Analyzed merging outcomes from company level and major business level and the final report got 2nd highest mark in class.

House Price Prediction using Machine Learning Technique Waltham, USA

• Scraped data from Airbnb using selenium and python; cleaned data, including selecting relevant features using regular expression and dealing with time variable using pandas
• Conducted Training-Validation-Test split; Filled missing values using two machine learning techniques (PCA and KNN)
• Built regression models using ridge and lasso regularization techinique and principal component regression to:
  1) reduce the dimensionality of the explanatory variables;
  2) predict house price.
• Presented data visualization using word cloud in python
• Created a website in the final presentation for the project

Estimating VaR of Stock Price Index (CSI300) Waltham, USA

• Conducted literature review and constructed our research structure
• Downloaded daily price of 10 assets from Investing.com, constructed full dataset by merging the data on the date index of the target asset(CSI300)
• Estimating VaR by modelling the volatility of stock return using conventional MA, EWMA, and GARCH(1,1) model, with the optimal parameter estimated using maximum likelihood function
• Estimating VaR by predicting daily loss of stock return using four machine learning algorithms, including Regression with Ridge/Lasso paneity, Random Forest, Gradient Boosting Regression, and Recurrent Neural Network
• Compared the estimating accuracy using back testing

SKILLS

Data Modeling: Machine Learning Algorithms, Deep Neural Network, Data Warehousing, Predictive Analysis, Data Analysis, Data Visualization, Troubleshooting

Program Language and Computer Software: Python, MySQL, PostgreSQL R, Tableau Software, Advanced Microsoft Excel

Languages: Chinese(Native)

Other: Photoshop, Premiere Pro