646-***-**** firstname.lastname@example.org Jersey City, NJ 07310 linkedin.com/in/minzhi-maria-meng-713b5a187 EDUCATION
New York University, New York, NY Sep 2018 – May 2020
• Master of Arts in Economics (STEM), GPA: 3.89
• Relevant Coursework: Applied Statistics & Econometrics; Math for Economists; Economic Analysis of Law; Corporate Finance
• Teaching Fellow at Stern School of Business Economics Department (3 courses: e.g., Data Bootcamp; Econometrics with Python) Shanghai
University of International Business and Economics, Shanghai, China Sep 2013 – May 2017
• Bachelor of Economics in Finance (Concentration: International Banking), GPA: 3.85
• Outstanding Graduate Award, May 2017 (Top 3%); Academic Excellence Awards, all semesters 2013 - 2017
• Vice President of Student Union, School Volunteer Leader, responsible of organizing large international volunteering activities SKILLS
• Software and Programming: Python, SQL, Tableau, Bloomberg Terminal, SAP, R, STATA, ArcGIS, Microsoft Suites
• Certificates: IBM Data Science Professional Certificate; Bloomberg Market Certificate; Excel Skills for Business Certificate; Certificate of China Accounting Professional; Certificate of China Securities Professional
• Language: Bilingual – Mandarin
Revelio Labs New York City, NY
Data Analyst Intern Jan 2020 – Present
• COVID-19 Impact Analysis
- Analyzed 1000+ companies workforce data before and after coronavirus outbreak through SQL and Python.
- Evaluated the risk of each company to COVID-19 by measuring the exposure to virus and company’s adaptability.
- Designed company score that rates each company’s risk to COVID-19, delivered the result as a standalone product that tracks the vulnerabilities of each company as well as the impact on broader economy.
• Workforce Dynamic Analysis
- Generalized companies’ comparative workforce reports as second-hand information for investors to evaluate a company.
- Processed million-row data from CRSP and other databases, merged various tables and conducted analyses through SQL.
- Trained econometric models to estimate the stock return by applying scaling methods and using moving average aggregation of company’s hiring rate, attrition rate, etc.
New York International Capital, LLC New York City, NY Investment Banking Analyst Intern, Global Investment Banking Division July 2019 – Sep 2019
• Carried out potential 5+ M&A deals as team leader; identified 50+ qualified buy-side clients after performing extensive market research; prepared 10+ pitch books using Excel and Tableau; directly reported project status to department director on daily basis
• Assisted team executives in coordinating meetings with buy-side and sell-side clients; collaborated with cross-functional teams, presented deal proposals and pitch book information to investment bankers, IT, and sales teams ZheShang Securities CO., LTD Hangzhou, China
Financial Analyst Intern, Bond Investment Banking Department Jan 2018 – May 2018
• Facilitated process of $1.5 billion worth corporate bond issuance; worked with 5+ team members to review details of financial statements through field survey; collaborated with external accounting and law firms to ensure accuracy for SEC submissions
• Participated in bond pricing and risk assessment and assisted in writing bond prospectus; created spreadsheet templates to automate procedure of financial analysis by applying functions such as VLOOKUP, Pivot Table and VBA, reducing future work time by 20%
Trading on Talent: Human Capital and Financial Performance Feb 2020 – Apr 2020
• Using Revelio Labs’ workforce data, explored relationship between stock performance and company’s human capital, especially turnover and employee skillsets; Analyzed employment and education trajectories of 2000+ US public company employees for period of 2009 – 2019. The updated project result was further transformed into the regular report to the clients. Attractiveness of a Metropolitan Statistical Area for Millennials Oct 2019 - Dec 2019
• Using US Census Data, applied Fixed Effect model to investigate the effects of factors on millennials choice of relocation from 2012 to 2017, factors including real GDP, education, nightlife entertainment, housing price. Aggregated 4G large data (over 3.5 million household records) through Python, explored various panel models in Stata. The project presented a new perspective that millennials take entertainment activities into consideration of relocation.