Data Scientist, Data Analyst. SQL, R, Python, Power BI

Xinqi Liu

Email: *****.***@*******.*** Phone: 513-***-**** LinkedIn: linkedin.com/in/xinqi-liu-b362b4156/ Objective

Experienced data analyst with 2 years of work experience in data analysis and business operation. Skilled in SQL, R, Python and data visualization tools. Seeking for data analyst and data scientist positions. Skills

Software: SQL (3 yrs), R (4 yrs), Python (1 yr), Power BI (2 yrs), Excel (PivotTable) (2 yrs), Power Point (3 yrs) Data Management: A/B Testing, Data Visualization, Machine Learning, Time Series, Experimental Design Work Experience

Data Analyst Oct 2019 – Present

Microsoft Commerce Team via Pactera Technologies, Inc. Redmond, WA

Analyzed millions of payment data for Microsoft products by SQL.

Developed A/B test experiments of dunning payment data for consumer products (Xbox, Office 365), the treatment group increased half year revenue by $1M in comparison. Generated R markdown template for similar and repeated experiments, saved the reporting and visualization time by 70%.

Monitored and Analyzed the payment anomaly incidents for consumer and commercial KPIs, provided the timely and sufficient analysis and operation suggestions, supported monthly business reviews.

Created Azure non-payment Power BI dashboard to keep in track with uncollected payment and to distinguish fraud and non-fraud actions, mainly focused on large market and top issuer groups.

Developed and maintained the R Shiny App of cost of payment model to explain the CoP MoM changes.

Generated CSV ad hoc reports of redemption and spend data for supporting business operations .

Maintained services and functions of SQL Server and Power BI Service for the entire team (present admin). Microsoft Azure Build Team via Pactera Technologies, Inc. Redmond, WA

Imported data from Microsoft Azure and OData to Power BI. Used DAX to create columns and measures. Generated customized and real-time data visualization reports, helped the team to monitor the bug status.

Created reports for daily, sprint and monthly time stages, provided statistical insights for further decisions.

Explored Kusto database to extract valuable information (incident managements, user records). Project

Machine Learning Project: TED talk comments prediction May 2019 Miami University Oxford, OH

Web scraped, loaded and cleaned the raw data of TED talk. Created new variables of sentiment scores.

Performed a Leave-One-Out Cross Validation study on several models (dimension reduction, tree-based models, k-nearest neighbors), predicted TED talk comments for testing dataset using the feature variables.

Summarized the results of prediction and determined the best predictive models (RMSE), selected important variables for boosted tree model by VIMP. Presented proper report by R. Education

Miami University, Oxford, Ohio Aug 2017- Oct 2019

Master in Statistics GPA: 3.72/4.0

China University of Petroleum, Shandong, China Aug 2013 - Jul 2017 B.S. in Chemical Engineering and Technology GPA: 3.2/4.0

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