Data Analyst Engineer

Yinhe (Luis) Lu

adcm53@r.postjobfree.com 858-***-**** New York https://yil479.github.io/luislu/

EDUCATION

Columbia University(GPA: 3.75 / 4.0) New York, NY

M.S. in Data Science Aug 2019-Dec 2020

● Core Coursework: Machine Learning, Data Visualization, Recommendation Systems, Computer Systems, Data Structure, Probability & Statistics, Data Modelling & Analysis University of California, San Diego San Diego, CA

B.S. in Cognitive Science specialized in Machine Learning and Computation(Major GPA: 3.83 / 4.0) Aug 2015-Jun 2019 PROFESSIONAL EXPERIENCE

DSI Scholar New York, NY

Data Analyst Intern Jan 2020– present

● Developed a Flask App hosted on Google Cloud for automating the classification of 25k comments into categories for evaluating students’ performance in Residency at Medical School

● Built interactive visualizations of the predicted data and sentiment analysis using Tableau CITIC Capital Beijing, China

Data Analyst Intern Jul 2018 – August 2018

● Conducted time-series models and utilized forecasting intervals in the detection of anomalies to identify trends in online payment and drove product roadmap by presenting insights to stakeholders.

● Helped design, define and launch advanced mobile apps for Beijing Public Services to provide more convenient and advanced payment methods and compute daily benchmarks for anomalies in online user experience monitor, increase online sales(up to 10% per product).

● Reinforced workflow automation by using SQL and bash scripts to reformat backlog, effectively saving over 3 hours of deployment time per day.

Mobe Wash San Diego, CA

QA Engineer Intern Jul 2017– Sep 2017

● Designed an interactive dashboard in Tableau for data reporting and provided recommendations for process improvement.

● Co-developed an interactive Flask app for visualizing data and sentiment analysis to predict customer behaviors, increased user base by 300%.

● Managed SQL and CartoDB to identify the correlation between customer traffic and community distance, and helped the product manager to identify potential customers.

PROJECT EXPERIENCE

Columbia University Data Science Hackathon Competition 1st Place (2019)

● Performed detailed data analysis on retail store datasets (Wholefood, Trader joe's, Sprouts) containing 20+ factors that can affect retail store customer traffic.

● Applied multiple regression supervised models such as KNN, decision tree, random forest, and concluded four most important variables from PCA analysis and outputted final demo consistent with the goal of data analysis to predict customer traffic given the input of store location

● Led a team of 4 people and presented final solutions in front of representatives of sponsor companies (Facebook, Wolfram Alpha, NYC data science academy, etc.)

Prediction on Yelp user ratings - Python, Spark, ScikitLearn

● Conducted data cleaning and variable selection to ensure meaningful analysis based on over 6 million user reviews.

● Designed a recommender matrix using KNN, Non-negative matrix factorization, Factorization machine, and Wide&Deep to predict the ratings of users of a certain business and reduced RMSE score by 20% compared to the baseline model.

● Evaluated model performance by comparing predicted user rankings of the business to true rankings, and measuring the model performance on different segmentation of users and business. Stock analysis and forecasting - R, D3, Shinyapp

● Explored ways of forecasting individual stocks within the portfolio and improve the return of the entire portfolio by 15% through different methods including factor models, Monte Carlo Simulations.

● Created time-series stock market data visualization and real-time stock market return portfolio SKILLS

Python(Pandas, Sklearn, Numpy, Tensorflow), Spark, R, Java, C#, SQL, Javascript, HTML, Hadoop, Node.js, Git, Recommender System, Machine Learning, Neural Network

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