Data Analyst/ Data Scientist

Alan Luo

**** **** **, **** ****** City, NY, ****1 480-***-**** adhus6@r.postjobfree.com

SUMMARY

A business-minded data scientist who won Kaggle silver medalist and with nearly 2 years of experience executing data-driven solutions to increase efficiency, accuracy and utility of internal data processing via Python, R, SQL & Tableau. Experience at building complex models and doing experiment to deliver insights and implement action-oriented solution to complex business problem. Looking to apply the same knowledge to real-world business problem SKILLS

Programming Languages & Software: Python (Sklearn, Pandas, Numpy, Keras, H2O, Matplotlib), R, SQL(MySQL, T-SQL), ERStudio, Tableau, Hadoop, Spark, AWS, Bloomberg, Advanced Excel (Pivot Table, Vlookup) Machine Learning: Linear Regression Methods(Lasso, Ridge), Logistic Regression, Random Forest, Gradient Boosting Machine, K- means, Isolated Forest, PCA, neural network

Analytics: Exploratory Data Analysis, Regression, Classification, Clustering, A/B Testing, Funnel Analysis, Cohort Analysis, Time Series EXPERIENCE

Overseas Students Services Corporation Overseas-Study Consultant and Life Services Company Data Analyst (Full-Time)

New York, NY

Feb 2020 – Present

• Performed and supported various A/B tests for OSSC Insurance product based on retention rate, funnel analysis; translated the findings into business recommendations and feature launch decisions

• Built Extract-Transform-Load (ETL) to calculate the main KPIs for products and troubleshoot data issues in the data pipline

• Extracted relevant user data (500K+) via writing SQL queries and analyzed users’ behavior on different social media to customize audience strategy, enhancing engagement by 30% and improving 0.4% of conversion rate

• Visualized the results using Tableau and collaborated with product manager to determine short-term and long-term revenue tradeoffs, and setting operational goals

State Administration of Taxation Chinese Governmental Tax Agency Beijing, China Data Scientist (Full-Time) May 2019 – Aug 2019

• Participated in Corporate Tax Risk Tracking & Evaluation project, worked with tax inspection department and engineer group to build a corporate tax tracking platform

• Improved performance of reporting process via writing SQL queries to extract relevant data (over 1M rows), building ETL to generate a summary table and creating Tableau dashboard

• Conducted corporate tax research and built machine learning model using Python (600K rows) and optimized the prediction model to get a result of 0.89 Recall rate and launched model to enable tax inspection department to more accurately track abnormal corporate, leading to a 80% boost in efficiency

• Created strategy and suggested actionable decision via Tableau for Risk Control Department by building interactive dashboard using Tableau, increasing the number detected companies that exist tax evasion AuraSource Inc Metal and Clean Energy Technology Company Phoenix, AZ Data Analyst (Full-Time) Jan 2018 – Dec 2018

• Performed commodities (metals) research and analytics with Python to build market prediction models using machine learning models, achieving 15% more accurate prediction of performance than previous

• Aggregated commodities indicators from Bloomberg terminal, extracted data (past 20 years historical data) using SQL, and conducted preprocess by data cleansing, feature selection, parameters tuning, validation, etc.

• Collaborated with engineers for a dashboard project that increased accessibility and usability of presenting results

• Delivered the model results and insights using Tableau for C-suite and resulted in a saving 12% cost of purchasing mine based on forecast of market trend

PROJECTS

Kaggle Competition ASHRAE (Silver Medalist, top 3%) – Great Energy Predictor III Oct 2019 – Dec 2019

• Used Python (Sklearn, Pandas, Numpy) to build prediction models of metered-building energy usage using over 1,000 buildings over a three-year timeframe (over 2 million data rows) and achieved top 3% ranking of 3600+ teams

• Performed data cleaning, generated “magic” feature and applied weight correction for the ensemble Machine Learning Model to reduce 32.5% RMSLE (from 1.4 to 0.945)

EDUCATION

Columbia University New York, NY

M.A. in Statistics (STEM, Data Science Track) GPA: 3.5/4.0 Feb 2020 Coursework: Advanced Machine Learning, Database System, Computational Statistics and Data Science, Experimental Design Arizona State University Tempe, AZ

B. S. in Business Data Analytics B. A. in Business Sustainability (Double Major) GPA: 3.9/4.0 May 2018 Coursework: Big Data (Graph theory, AWS), Data Modeling & Mining, Linear Algebra, Probability Theory

Contact this candidate