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Data Financial Analyst

New York City, NY
December 30, 2018

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Frank (Zijing) He

**** ************ ****, ***.****, Dallas, TX75206 214-***-****


Southern Methodist University, Cox School of Business Dallas, Texas

Master of Science in Business Analytics GPA:3.7/4.0(STEM eligible; sponsorship not required until 2021) Jul017 - May 2018

Zhejiang University of Finance& Economics Hangzhou, China

Bachelor of Science in Business Administration GPA: 3.83/ 4.0 Sep 2013 - Jun 2017

Shih Hsin University Taipei, Taiwan

Exchange Program-Finance GPA: 93/100(Top 1%) Sep 2015 - Feb2016


SQL Power BI Tableau R Python Oracle Hadoop Alteryx KNIME Access Excel (Pivot table, VBA) SAS MDS


Apartment Investment and Management Co (Aimco) Denver, CO

Data Financial Analyst Sept 2018 - Present

Wrote complex SQL query in SSMS to extract unit information and create metrics to track unit redevelopment status

Created weekly RD/leasing summary dashboards in power BI to visualize the current/history status for different properties

Worked with IT team to integrate separated databases into Aimco online reporting services (SSAS)

UDR, Inc Denver, CO

Financial Analyst Intern in Business Analytics June 2018 – Sept 2018

Created efficient frontier in R with 42 markets’ annual return from 1988 to 2017 to help company make better portfolio strategy

Constructed panel data in R, incorporated the market-specific variables using forward selection across the sample of Metropolitan Statistical Areas (MSAs) into six-factor predictive model to drive market rankings and forecast potential rent growth

Used Alteryx to clean the spatial file and properties’ data; Utilized Tableau to map all the submarkets polygon with all multifamily properties data in New York city to assist the board making decisions about the future land use and development plan

Created key word searches that screen the properties and peer properties on the reputational website to better understand the pressure points; Used text mining and sentiment analysis in SAS to dig into the reasons for customers’ satisfaction

Sparkhound-SMU MSBA Analytics Practicum Dallas, Texas

Student Business Intelligence Analyst Jan 2018 – May 2018

Collaborated with collision repair company to optimize the employee turnover rate for technician and service advisors nationwide

Developed complex SQL queries using common table expression (CTEs) and temporary tables to get payroll and timesheet data

Classified employees in to three categories using k-means clustering models in R studio based on performance metrics

Manipulated the data and build logistic model Using R to predict the probability of employee’s turnover based on center level

Visualized the status and prediction of employees’ turnover rate by building dashboards using Power BI and report to manager


Business Intelligence

Created SQL queries to extract business insights from data warehouse of a bicycle company

Analyzed database physical structure and functional requirements of virtual users

Developed ETL process for production data utilizing Visual Studio, and built production data warehouse in SQL

Data Mining

Performance exploratory Data Analysis (EDA) of direct marketing campaign data for a Portuguese banking institution

Utilized Naive Bayes Classification in KNIME to predict the term deposit subscription and validated model with confusion matrix

Manipulated 366644 rows of hotel subscription data and partitioned them into training and validation dataset with KNIME

Used Neural Network Package in R to predict the hotel subscriber and evaluated the model using cross validation method

Predictive Analytics

Cleansed raw data to remove and replace missing values before data analysis

Applied linear regression model and maximum log likelihood, using SAS to handle endogeneity issue of the sales data and predict catalogue and internet sales for a retailer of educational software

Utilized R and employed 3 different statistical models including Shifted Beta-geometrics, Exponential Gamma, Weibull-Gamma with Covariates to capture the heterogeneity in different variables to model record album sales

Assessed and compared the fitness of different models to generate model reports and future album sales forecast


CFA Level 1(Passed,10A, Top 1%), CFA Level 2 Candidate CCA Data Analyst (in process)

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