Data Analyst Python

Bailing Fu

**** ******** ******, ** 715-***-**** *********@*****.*** https://github.com/BailingFu EDUCATION

Fordham University New York, NY

Master of Science in Data Analytics, GPA 3.4 Dec 2019

• Relevant Coursework: Data Mining, Machine Learning, Algorithm for Data Analytics, Big Data Programing, Cloud Computing, Data Visualization, Natural Language Processing, Deep Learning University of Wisconsin at Stevens Point Stevens Point, WI Bachelor of Science in Mathematics, Minor in Economics, GPA 3.46 Dec 2017

• Rewards: Thalacker-Trytten Scholarship; Dean’s list (2016-2017)

• Relevant Coursework: Complex Number, Topology, Number Theory, Discrete Mathematics, Personal Finance CORE COMPETENCIES

Skills: Python, SQL, Tableau, Excel, Spark, Hadoop, GCP, AWS, Microsoft Office, SAS, Linux Competency: Data Analysis, Database, Data Visualization, Machine Learnning, Deep Learning, Cloud Computing

& Platforms

PROFESSIONAL EXPERIENCE

New York Bay Capital New York, NY

Financial Data Analyst Intern Jun 2019–Aug 2019

• Established full-scale operating models and conducted including industry research, discounted cash flow (DCF) analysis, comparable company analysis and precedent transaction analysis

• Created descriptive and hierarchical graphs of revenue, debt and key margins in Excel and interactive annotated stock charts and distribution map in Tableau for companies like TSLA, Walmart and Del Monte

• Participated conferences with clients and assisted in making pitch books for buy-side and sell-side M&A transactions

PROJECT EXPERIENCE

Groupon Stock Strategy Recommendation Aug 2020–Sept 2020

• Conducted visualization and EDA using Pandas-Profiling and Tableau to detect data irregularities

• Established DeepAR, a Deep Recurrent Neural Network Auto Regression, on AWS Sagemaker to impute missing time series values

• Developed a sell recommended strategy based on a gross billing analysis which outperformed the equity research reports provided by two investment banks

Snagging Parking Spaces With Mask R-CNN Oct 2019–Dec 2019

• Decomposed video streams from CCTV and analyzed each frame in order to detect parking spaces, cars and empty parking spaces

• Accomplished car detection with Mask R-CNN, and utilized Intersection Over Union (IOU) to detect empty parking spots in Python

• Designed a SMS alert system by using Twilio which will inform user with real-time message Data Visualization and Cloud Analysis on NBA Log Feb 2019–Apr 2019

• Visualized NBA team locations on maps, conducted player age analysis, and displayed shot locations and results on a basketball court in Python using Matplotlib

• Utilized MapReduce on Hadoop and Spark in Linux environment to calculate fear score for each player parallelly when facing other defenders, and find out “most unwanted defender” for each player on NBA shot log data stored on HDFS on Google Cloud Platform

Predicting Hospital Readmission Rate for Diabetes Patients Oct 2018–Dec 2018

• Imputed significant missing values with regression and classification models, and utilized SMOTE, Bagging techniques to data imbalance in Python

• Applied ensemble methods such as majority vote and weighted vote to build strong learner based on classic algorithms including logistic regression, KNN, SVM, Bayesian, Decision Tree and Random Forest after feature selection and hyperparameter tuning, achieving 87% accuracy

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