Data Analyst Assistant

Zidu (Jack) Yin

**********@*****.*** 860-***-**** https://www.linkedin.com/in/jack-zidu-yin/ Stamford, CT 06901(Willing to relocate) Experienced Data Analyst with problem-solving, analytical thinking and communication skills. Accustomed to manipulating large data sets using SQL, Python, and R, and collaborate with teams to conducting technical analysis for non-technical audiences. Technical Skills

Programming languages: Python (Pandas, NumPy, scikit-learn), SQL (join, windows function, subqueries), R, VBA Tools: Tableau, Advanced Excel (Pivot Table, macro, VLOOKUP, VBA), Access, MySQL, SAS, JMP, PowerBI, Visio Analysis Techniques:

• Linear Regression (OLS & GLS), Classical & Penalized Regression (Lasso, Ridge), Clustering, K-Means, Random Forests, Neural Network, Naïve Bayes, Ensemble Modeling, Discriminant Analysis, KNN, PCA, CNN, LSTM, XGBoost

• Statistical Significance, Confidence Intervals, Hypothesis Testing, A/B Testing, Segmentation Analysis, ETL, NLP Courses: Predictive Modeling, Statistics, Database Application, Deep Learning, Linear Algebra, Visual Analytics, Accounting Work Experience

The University of Connecticut, Stamford, CT

Assistant Research Scholar-Nighttime light and population dynamics Project (Python) June-Aug 2020

• Shuffled data randomly, performed normalization and PCA on variables, and partitioned data

• Fitted a baseline model, a random forest with hyperparameter tuning and a neural network with dropout method

• Performed 10-fold cross validation on the training dataset and applied models to the test dataset

• Evaluated models by comparing MAE of each model, and chose the best model to identify patterns for future decision making Academic Experiences

The University of Connecticut, Stamford, CT

Graduate Teaching Assistant: Business Decision Modeling using Excel Jan-May 2020

• Researched how to write simple VBA codes and run a macro from another macro, and made tutorials for students by writing instructions in MS Word and recording videos in MS PowerPoint

• Provided guidance for 50 students about how to use pivot table and functions like VLOOKUP, SUMIF, MATCH, etc.

• Scored assignments and exams about supply chain, linear optimization, Monte Carlo Simulation, and sensitive analysis

• Assisted students in creating formulas and designing financial models Football Market (Tableau) Feb-Apr 2019

• Created a Radar chart to analyze 20 thousand football players’ abilities and compare at the same time

• Produced a dynamic table that incorporated players’ information (weekly wages, values) with conditional filters

• Made a presentation by combining all the things in a dashboard for better visualization and advice for simulated managers Fashion Company Marketing Strategies (Oracle SQL, MS Visio) Oct-Nov 2018

• Gathered data from several fashion companies and designed ER diagram using MS Visio

• Created 18 data tables in Oracle relational database and inserted records into the tables

• Wrote complex SQL queries to extract information of sales and profit grouped by campaigns for better marketing strategies Internship Experience

Potoo Solutions (eCommerce Consulting Company), Norwalk, CT Graduate Analyst Consultant (Python) Jan-May 2020

• Aggregated data with 10M records, encoded text variables into dummy variables, applied feature engineering to generate useful variables, and partitioned the data

• Developed Random Forest, Decision Tree, Neural Network and Multi-label logistic regression (best model)

• Selected the Multi-label Logistic regression with almost 80% accuracy to predict which source sellers get their product from.

• Analyzed p-values and coefficients of variables, and made a report to provide further recommendations for the stakeholder Agricultural Bank of China, Beijing, China

Data Analyst-Credit Card Score (R Programming Language, SAS) July-Sept 2016

• Explored customer credit data with 150 thousand records, imputed missing data with KNN methods and deleted outliers

• Analyzed variable distributions and correlations, partitioned the data, and built the logistic regression model with AUC of 0.81

• Transformed the model with WOE method for better financial understanding and built the final score table

• Clustered customer data to analyze their preference for financial products and services using SAS E-miner Educations

University of Connecticut School of Business

Master of Science in Business Analytics and Project Management (S.T.E.M) GPA:3.8/4.0 May 2020 Jiangxi University of Finance and Economics

Bachelor of Economics, Finance GPA:3.5/4.0 June 2018

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