JINJIN WU

Objective: Data Scientist Intern

443-***-**** adwbn0@r.postjobfree.com Arlington, VA

EDUCATION

The George Washington University Washington, DC

Master of Science degree: Statistics September 2022 Nanjing Normal University Jingshu, China

Master of Science degree: Psychology September 2018 Information College Huaibei Normal University Anhui, China Bachelor of Science degree: Applied Psychology September 2013 PROFESSIONAL Experience Washington, DC

Sale’s Prediction January 2023- February 2023

Background: Rossmann store managers are tasked with predicting their daily sales for up to six weeks in advance. The task is to forecast the sales with historical sales data for 1,115 Rossmann stores.

• Performed data preprocessing and feature engineering with pandas and matplotlib

• Implemented XgBoost, GBDT and Random Forest model, conducted grid search to optimize the hyper-parameters. XgBoost achieved 17% RMSE reduction compared with other tree models.

• Extracted the timestamp features which helped reduce 6% RMSE. Washington, DC Customer Segmentation January 2023-February 2023

Background: To understand the customers who can be easily converge so that the sense can be given to marketing team and plan the strategy accordingly.

• Conducted EDA on binary and unary variable analysis via F-test, normalized the each feature of the customers into the same scale

• Implemented XgBoost, GBDT and Random Forest model, conducted grid search to optimize the hyper-parameters. XgBoost achieved 17% RMSE

• Conducted EDA on binary and unary variable analysis via F-test, normalized the each feature of the customers into the same scale

• Implemented K-means with sklearn to cluster customers with different settings of K, and selected the optimum value of K as 5 using the Elbow Method, result in a balance between number of clusters to form and inertia The Compensation of the Wrongly Convicted –An Analysis of Exonerations. Washington, DC Project August 2022-Deceber 1 2022

Background: To determine factors associated with exonerees seeking and receiving compensation.

• Performed data cleaning with volume 3302 via SQL including removing the outliers and imputing missing values

• Conducted descriptive analysis and differential analysis using R and Python, acquired ROC curve, odds ratio, and 95% CI of gender, area, political affiliation, DNA evidence, etc. with compensation

• Derived general linear model, used stepwise methods to find the best mode INDEPENDENT RESEARCH

Occurrence and Development of Gender-Color Metaphors in Children Nanjing, China September 2020-April 2021

Background: To explore the occurrence time and development characteristics of children's gender color metaphor through children's color preference

• Designed the behavioral experiments and used pilot experiment to evaluate reliability and validity

• Used PivotTable to process data, and performed Variance Analysis on the children's color preference under various scenarios

• Visualized selection results of children by Tableau to discover the law of children’s gender color metaphor development The Influence of Parenting Patterns on Children's Self-confidence Nanjing, China September 2019-January 2020

Background: To find the relationship between parental acceptance-rejection, children’s emotion regulation, and home-school cooperation

• Collected 2297 preschool children cases, used Process-Person-Context-Time model and constructed with PROCESS macro

• Standardized continuous variables and computed the interaction terms from these standardized scores.

• Used the bootstrapping method based on 5000 samples to obtain the bias-corrected confidence interval

• Carried out descriptive analysis on the model dimensions of democracy, family, partner, and confidence by SPSS TECHNICAL AND LINGUISTIC SKILLS

Programming and Libraries: R, Machine Learning, Python, Excel, SPSS, SQL, HTML, Pandas, Tableau Languages: Chinese (native), English (advanced)

Contact this candidate