Rachel
可提供服务：
、文书修改
、文书写作
、全套申请
、选校定位
、网申
、申请咨询
、签证咨询
可服务区域/国家：
、美国
已助力 27 人实现梦想
准时率：99.9%
综合评分：
简介
本科毕业于美国前三十的伊利诺伊大学香槟分校，统计学与工业工程运筹学双学士学位，DIY完成本科硕士申请。研究生主申BA和DS，收到USC，Duke，哥大，WUSTL，UMN，UT Austin，USF等学校的offer。研究生毕业于德州大学奥斯汀分校Business Analytics专业（BA第一的神校）。现就职于美国旧金山downtown一家Fintech公司，职位是数据分析师。经历过在美转专业申请的血泪史，具有丰富的统计/数据科学/商业分析申请经验。
专长
实习经历
Company – Data Analyst Intern
● Collaborated in cross functional team, gathered data from 1.5M insurance services with SQL, conducted statistical analysis with SAS and visualized them with Tableau dashboards
● Identified how roadblocks of healthcare insurance claims change with age and provided data-driven solutions for members to prepare for most frequently denied medical procedures to reduce claim denied rate
工作经历
Company – Data Analyst, San Francisco, CA
● Worked cross-functionally with Risk Management and Operation teams extracting, manipulating and analyzing First Payment Delinquency Performance of over 149K+ personal loan records with SQL and built visualization dashboards on Mode Analytics to monitor delinquency performance and recognize the early signal of potential charge-off
● Took the initiative to analyzed loss rate trending, mined delinquency behaviors to differentiate applicants, conducted Time Series analysis in Python to predict future delinquency performance and successfully achieved 83% accuracy
● Conducted Feature Selection and Segmentation Analysis with Logistics Regression and Classification Trees using Python to find important and stable features for application model, handled unbalanced data with K-fold cross-validation and resampling, and reported significant findings for business decisions
Company – Data Scientist Intern, Austin, TX
● Predicted customers’ next transaction based on their previous transactions with large data set of 175K+ customers using LSTM model, input transaction sequence and output with probabilities of transactions, and obtained 69% accuracy for fraud detection
● Gained business insights via Exploratory Data Analysis with Tableau, and validated the existence of transaction patterns
● Conducted word embedding (Word2Vec and Doc2Vec) on transaction series, used cosine similarity to cluster customer transactions and segment customers, and utilized T-SNE to visualize the clustering on Google Cloud Platform
Company – Supply Chain Data Analyst, Morton, IL
● Led 5 other interns to optimize the yard and successfully improved the picking process by 41%
● Manipulated database of 10K+ historical data, retrieved data with SQL, built predictive model on seasonal differences, and visualized relationship between items with R
● Implemented integer-programming models with C++ and CPLEX, simulated picking process with Python, and built an Excel-based tool to realize repeatability of the optimization for future projects
评价
IvyBridgedu（常春桥留学） - 留学行业的规范者与引领者
