Data Python

Jing (Julia) Lyu

Brooklyn, NY ******@***.*** 347-***-**** www.linkedin.com/in/jinglyu33

EDUCATION

New York University, Tandon School of Engineering Brooklyn, NY M.S. in Financial Engineering GPA: 3.8/4.0 05/2019

• Coursework: Machine Learning, Financial Computing (OOP), Risk Management and Asset Pricing

• FRE (Financial and Risk Engineering) Club, Finance Club Xiamen University Xiamen, China

B.S. in Mathematics and Applied Mathematics GPA: 3.5/4.0 07/2016 B.S. in Mathematical Finance GPA: 3.7/4.0

• Coursework: Statistics, Econometrics, Time Series Analysis, Probability Theory, Stochastic Process

• Awards: First Class Scholarship 2012-2014, Dean’s list 2014-2016 PROFESSIONAL EXPERIENCE

ICBC Financial Services New York, NY

Credit Risk Analyst Intern, Data Management 10/2019-Present

• Build statistical models such as Logistic Regression, Random Forest and Gradient Boosting Decision Tree in Python to predict the probability of default for counterparties using quantitative and qualitative risk measures

• Perform feature selection & combination using Lasso Regression, Ridge Regression and PCA which improves the model performance by 15%

• Create automated data pipelines to perform data cleaning, transformation, quality checks using Python and SQL

• Develop a database to store financial statements of broker-dealers, hedge funds and mortgage REITSs clients

• Perform model data collection, data point assessment and user testing on the default risk models

• Automate risk table generation, industry aggregation and balance sheet account reconciliation using Excel VBA

• Work with IT team in developing data warehouse and risk report for repo and securities lending clients

• Design and create interactive data visualization dashboards in Tableau to monitor counterparties’ risk exposures Changan Fund Management Shanghai, China

Intern, Data Analytics 06/2018 - 08/2018

• Developed data ETL processes to extract data from vendors, clean and store data into SQL database using Python

• Predicted stock returns based on financial indicators using models such as Linear Regression and Lasso Regression

• Built time series models to predict macro indicators such as unemployment rate, quarterly GDP, and generated interactive monthly report in Tableau to help portfolio managers analyze the trends of the macroeconomy Tebon Fund Management Shanghai, China

Intern, Data Analytics 03/2017 - 07/2017

• Conducted data transformation processes such as filling missing data, outlier detection and merging data tables

• Used excel functions and VBA Marco to automate report generation to support a fund-of-fund project

• Classified fund products using clustering methods such as K-means and KNN based on fund information in Python PROJECT EXPERIENCE

Sentiment Analysis of ETF statements

• Built web scrapers using BeatutifulSoup in Python to collect financial statements from ETF providers’ websites

• Conducted word tokenization, stemming and lemmatization to convert text data into standardized bag of words

• Performed sentiment analysis on risk chapters of statements using NLTK, and plotted the trends of the sentiment SKILLS

Programming: Python (Pandas, Sklearn, NumPy, Seaborn, Scrapy), SQL, Excel VBA, MATLAB, C/C++ Data Science: Linear Regression, Time Series, Machine Learning, Data Wrangling, Data Visualization

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