Yue (Elsie) Liu

Yue (Elsie) Liu

Master’s Student

Boston University

Hello world! I am a master’s student at Boston University majoring in Applied Business Analytics, graduating in May 2022. Previously, I received my M.S. in Financial Management from Boston University in December 2020.

I am actively seeking full-time entry-level work opportunities in Business Analytics, Data Analytics, Finance, or other related fields. Feel free to reach out to me if you are hiring!

I am experienced in developing intelligent business solutions from business insights, analytical tools, and team collaboration. My skills and certificates include SQL, Python, R, Advanced Excel, Tableau, PowerPoint, PowerBI, CFA Level I.

Interests

  • Data Analytics
  • Business Analytics
  • Finance

Education

  • M.S. in Applied Business Analytics, 2021 - Present

    Boston University, Boston, MA

  • M.S. in Financial Management, 2019 - 2020

    Boston University, Boston, MA

  • B.S. in Finance, 2015 - 2019

    Nanjing University, Nanjing, China

Work Experience

 
 
 
 
 

Business Analyst (Capstone)

National Grid

Jan 2022 – Present Waltham, MA

  • Reduced charging station costs for electric vehicle fleet in Massachusetts and lessened load impact on local grid by optimizing the charging cycles based on exploratory analysis of historical energy load data, charging session data, and daily mileage data.
  • Identified the best charging rate and duration for electric vehicles by formulating a constrained optimization model to fulfill predicted energy demand at the lowest possible cost.
  • Decreased charging at peak time by producing Tableau dashboards detailing the hourly regional load at each charging station based on historical energy load data gathered from government websites.
 
 
 
 
 

Technology Consulting Intern

Ernst & Young

Jun 2021 – Sep 2021 Beijing, China

  • Strengthened management’s understanding of company status for State Grid (the world’s largest energy company as our client) by designing dashboards for 10 business scenarios and delivering them to 5+ teams.
  • Highlighted cost-saving opportunities by creating a Tableau geospatial dashboard for suppliers’ credit-status distribution which allowed for more efficient detection of overdue events from each operation stage; terminated untrustworthy contracts accordingly.
  • Boosted discovery of non-compliant events 10%, when compared to previous inspection method, by revamping the risk detection metrics and mechanism when performing compliance inspection on a top real estate client; identified the 20 riskiest subsidiaries.
  • Streamlined consumption of business data for decision-makers by identifying the most impactful metrics, mapping out trends, and producing intuitive visualizations.
  • Increased working efficiency by liaising between cross-functional teams – managed project progress, streamlined workflow and feedback process, verified data sources, and ensured prompt delivery.
 
 
 
 
 

Teaching Assistant

Boston University

Sep 2020 – Jan 2021 Boston, MA

  • Instructed a class of 40+ students on financial regulations and ethics in practice involving in-depth case studies.
  • Helped with designing tutoring materials, grading and Q&A; organized weekly write-up sessions for case analysis.
 
 
 
 
 

Financial Analyst Intern

Industrial Bank Co., Ltd.

Jun 2018 – Sep 2018 Zhenjiang, China

  • Strengthened client company’s understanding of its industry status by writing a research report demonstrating the cyclical pattern and key influential factors of the product price on the market complete with visualizations and in-depth analysis.
  • Improved investment-decision making by applying a DCF model on metrics identified during industry analysis to predict future stock prices and pinpoint the most cost-effective entry time.
  • Increased the usability of data collected via Wind database and web scraping through cleaning and exploratory analysis; identified trends and factors driving profits by creating visualizations.
 
 
 
 
 

Sales Analyst Intern

Huatai Securties (HTSC)

Jun 2017 – Sep 2018 Nanjing, China

  • Achieved an incremental acquisition rate of 5% and successfully sold derivatives of $50,000 by introducing a trigger campaign for use in the customer acquisition process.
  • Improved matching of financial products to clients by performing classification on 1,000+ accounts based on risk preference, transaction activity level, and amount of funds.

Projects

 
 
 
 
 

Jane Street Market Prediction Competition (Rank 204/4121, Top 5%)

Kaggle

Dec 2020 – Feb 2021 Online

  • Predicted future stock market performance based on past data and developed an investment strategy to gain a maximum return by training neural networks using PyTorch; boosted prediction accuracy by model ensemble.
  • Improved quality and usability of over 2M high-dimensional anonymized stock market data by using Python to perform preprocessing, normalization, and handle missing values and outlier data.
  • Identified key correlations of the data through visualization for feature engineering.
 
 
 
 
 

New York City Real Estate Analytics

Boston University

Jan 2020 – Jun 2020 Boston, MA

  • Predicted the potential profitability of opening a real estate business in different boroughs of New York City by performing constrained NPV optimization using GRG non-linear solver and identifying bottleneck constraints of profit.
  • Cleaned historical real estate data from New York City with R and performed K-Means clustering based on important KPIs (e.g. total transactions, average housing price) to adopt differential strategies for each district.

Contact

  • yltrulla [at] bu [dot] edu