Data Analyst Digital Marketing

Steve (Zhijie) Ren

Arlington, VA ***** 571-***-**** ***********@*****.***

SUMMARY

Motivated, teamwork-oriented and responsible Data Analyst with 2 years of experience doing meticulous and intensive work in digital marketing, analytical research, e-commerce optimization, natural language processing and other advanced analytics. Experience includes statistical modeling, machine learning, data visualization and data governance. Maintains an open mind for innovation with internal and external processes.

• Certification: Data camp Intermediate SQL degree

• Skills: SQL, Python (Sklearn, xgboost, etc), R, SAS, Tableau, Power BI, Google Analytics, Excel (Vlookup, Pivot Table, etc)

• Proficient in advanced analytics method including Correlation, Regression, Classification, Clustering, A/B Testing, etc. EDUCATION

The George Washington University Master of Science in Data Analytics 01/18 - 01/20 Related course: Data Mining, Data Visualization, Machine Learning, Introduction to Big Data, Data Base Management The State University of New York at Binghamton Bachelor of Arts in Mathematics – Actuarial Track 08/12 - 05/20 Related course: Calculus, Linear Algebra, Real Analysis, Number system, Introduction to Python WORK EXPERIENCE

Uniformed Services University of the health sciences Bethesda, MD Research Assistant Intern 03/20 – present

• Collecting and recording Data such as Nodule length and Nodule Area from more than 5000 CT images by MIM software.

• Doing A/B test to analyze the relationship between each feature and lung cancer from dozens of features.

• Constructing Decision Tree model for predicting if a patient has lung cancer. Found CT value reflected inside the nodule has highest weight in the model.

US Fitness Co., LTD Mclean, VA Corporate Data Analyst Intern 06/19 – 08/19

• Defined and determined key performance indicators and metrics such as EBITDAR, gross of memberships and personal training revenue, etc. to be analyzed for marketing decision and return evaluation.

• Utilized SQL to extract historical gym performance data from Oracle database and use Excel to establish a scorecard system for all gyms by calculating average, standard deviation of related metrics to identify the gym performance ranking that can demonstrate a strong recommendation impact and significant on operation.

• Acquired geographic data including market size, competitor strength data,etc by Google tools. Build up several prediction models including Linear Regression and XGBoost by Python to predict the impact of different geographic data on KPIs.

• Compared model accuracy based on goodness of fit. Predicted KPIs of three given locations by the best performing model whose RMSE was less than 20%. Suggested to build a new gym on the location with the highest predicted KPIs.

• Visualized the CRM data and developed a data-driven Tableau dashboard to inform optimization priorities and provided suggestions on location selection, audience demo, and consumer behavior. D.MCARK Information Technology Co., LTD Guangzhou, China Data Analyst 02/17 – 12/17

• Identified, analyzed, and executed large, compiled datasets from Taobao to generate consumer website behavior, content report and e-commerce digital assets performance.

• Led initiative to build machine learning models using historical data to predict customer segmentations; Focused on data profiling, feature engineering, and analyzing the factors affecting the lifetime value of the customer; Designed marketing strategies to help improve targeting accuracy and efficiency to drive incremental sales by 15%.

• Analyzed large dataset with 50+ features using SQL and Tableau to generate product sales dashboard; supported client’s marketing and sales strategy to provide useful operating suggestions. PROJECTS

Women Clothing E-commerce Reviews NLP Analysis 01/20 - 03/15

• Extracted, blended and analyzed 200K women clothing e-commerce reviews data and conducted a fraud detection to remove the fake reviews.

• Utilized TF-IDF methodology to optimization reviews’ tokenization categories and proposed a comprehensive neural network model by incorporating underlying information into document-level sentiment classification.

• Built a dynamic web-based app using Python and Streamlit to help e-commerce marketers get a better understanding consumer feedbacks about their products.

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