Data Analytics

MINGLU SUN

** ***** **** ***, *** York NY ***** 929-***-**** ******@*******.***

Data Scientist with 2 years of extensive experience with strong skills in quantitative analytics, problem solving, project management, and communication, as well as great teamwork. Aiming to utilize my experience, knowledge, and skills to help your company grow. EDUCATION

Fordham University, Gabelli School of Business New York, NY. 08/2016 - 02/2018 MS, Business Analytics, GPA 3.82

• Relevant courses: Machine Learning, Database Management, Text Analytics, Big Data, Web Analytics, Explanatory Model, Business Performance and Risk Management, Financial Programming and Application, Business Analytics for Managers Shandong University of Finance and Economics Jinan, China. 08/2012 - 06/2016 BA, Finance, GPA: 3.69

• Relevant courses: Risk Management, Economics, Investment, Econometrics, Statistics, Corporate Finance, Accounting WORK EXPERIENCE

Senior Technical Member, Design Lab, Fordham University New York, NY. 01/2017 – present

• Text Analytics - Constructed 2 domain-specific dictionaries and ran sentiment analysis by IBM Watson, then executed deep learning to classify earning ability of company based on Compensation Discussion of S&P 500 with 83% accuracy

• Financial Analytics - Carried out descriptive and predictive analysis of financial crimes, and developed a holistic database Business Analyst, NYC Department of Design & Construction New York, NY. 01/2017 - 12/2017

• Identified data quality issues, and directed data engineering and prediction modeling for 20-years of input-data

• Procured automatic ETL processes, identified effective attributes, and designed interactive dashboards and GUI software by Python

• Presented directly to managers regarding findings, and proposed recommendations on cost strategy implementation to reduce costs PROJECTS

Financial Modeling – Option Gleaner New York, NY. 08/2017 - 12/2017

• Developed Option Gleaner GUI software by Python tkinter based on crawled 25k+ tickers with options

• Built a web application by Python Flask to automatically download, filter, analyze and visualize European options United Nations – Prediction of violence for the Kenyan Election New York, NY. 07/2017 - 08/2017

• Led a team of 3 to establish 2 regression models to discern correlation between nature of events and violence for 47 counties

• Leveraged time series analysis to surmise riots occurring within 60 days after the election by using Prophet library in R

• Communicated with United Nations officers seamlessly in a virtual environment, and delivered technical analysis report Big Data - What does your lipstick say about you? New York, NY. 01/2017 - 05/2017

• Discovered relationship between Big 5 personality traits and colors based on 5.3GB data crawled from Twitter by IBM Watson Tone Analyzer, Amazon Web Services, and machine learning algorithms

• Applied clustering by PySpark to create 3 clusters of 25 colors, offering references for production of lipstick palettes

• Suggested brands launching sales promotion based on various personality distribution of customers Deloitte March Madness Data Crunch - Prediction of winners of 2017 NCAA New York, NY. 01/2017 - 03/2017

• Introduced 6 externally created variables to the original dataset, and after feature engineering utilized Ensemble Learning to stack machine learning models (K-Nearest Neighbor, Logistic Regression, Support Vector Machine, Neural Network) to predict the winner for each game, achieving 75% accuracy and winning the third place among 26 teams

• Designed informatics poster and flyer to visualize methodology, and presented findings in the final competition conference Database Management – Pharmacy Prescription Tracking System New York, NY. 08/2016 - 12/2016

• Engineered a pharmacy-tracking relational database by DB2 and Infosphere Data Architect

• Accessed DB2 from Python in IBM Bluemix environment and implemented all SQL queries for database operation and maintenance RELATED SKILLS

• Machine Learning: Experienced with Classification, Clustering, Feature Engineering, and Ensemble Learning

• Statistical Methods: Extensive knowledge of Time Series, Regression Models, Regression Diagnostics, Hypothesis Testing and Confidence Intervals, Principal Component Analysis, and Dimensionality Reduction

• Programming: Proficient in Python (NumPy, SciPy, Pandas, Seaborn, Scikit-learn, NLTK, Scrapy), R, and SQL

• Software: Proficient in Tableau, Spotfire, QlikView, Alteryx, SPSS, Oracle, MySQL, Hadoop (Hive, Map-reduce), and Excel

• Platforms: Familiar with Amazon Web Services, IBM Bluemix, and Google Cloud

• Certifications: Python MySQL from Scratch, Python for Data Analysis and Visualization

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