• Independently developed population components forecast model in R/SAS using a time series algorithm to predict Ontario's major cities' pop components change; Key findings on GTA non-permanent residents’ growth trends helped support college students’ recruitment strategy for senior management.• Developed and maintained an in-house model in SAS/SQL to evaluate financial performance at the program level, such as revenue, cost, and net contribution; Established a Tableau dashboard to visualize the most and least profitable programs by faculty, which helped support college enrolment targets setting strategy.• Coordinated college enrolment planning project; Reconciled enrolment targets between faculties and the Office of Registrar; Improved communication efficiency by conducting a customer-oriented approach, which facilitated project completion 2 weeks ahead of the deadline.• Identified a miss-calculated cross-college financial grant allocation; Reported timely to management by providing a detailed analysis, which supported the Finance department in correcting funding allocation.

• Developed advanced predictive models in R/SQL to forecast sales based on 5 years of historical customer trade promotion activities, seasonality, cannibalization, COVID-19 effect, etc., with an average accuracy of 91%; experimented with 1000+ price scenario simulations to support 2021 business planning decisions. • Independently designed Tableau visualizations (bar charts, scatter plots, promo calendar, etc.,) to interpret predictive model results for less technical teams; Automated business reporting routine by transitioning 35 Excel Pivot reports into Power BI dashboards, allow users to access and communicate for their purpose. • Utilized statistical analytics skills in product price optimizations for 10 key retail banners across Canada, optimized millions of revenues by developing retail promo strategies (bundles, flyer features, etc.,), presented precise analysis to customer buyers, delivered analytical reports 100% on time.

• Independently designed and built predictive regression models for stores strategic sales forecasting using R, with an average accuracy of 88%, which leveraged analytical automation and forecast efficiency• Maintained and updated system data including demographics, competition and sales using multiple applications, such as MapPoint, MS Access and MicroStrategy• Utilized Oracle SQL database management and SQL Developer software to ensure data integrity through raw data cleaning process with massive enterprise data• Designed, developed and enhanced in-house GIS applications using C#, .Net and VB• Performed ad-hoc analysis requested from various business units in the company, 100% delivered on-time

• Developed and verified in-depth theoretical hypotheses related to technological diversity and innovation performance based on quantitative patent data analysis• Processed raw data cleaning work with 9 million patent data with 117 attributes using R programming: corrected error records, standardized data format, removed unwanted and irrelevant observations, imputed missing values based on other observations, extracted the completed dataset to test the proposed hypothesis• Evaluated statistical model performances of linear, logistic regression, competing risk regression, proportional hazard regression, etc., to select the best prediction model based on data type and research interest• Presented research results and justified the methodological approaches through engaging a discussion with experts in the field

• Supported administrative and tutoring duties for the Strategical Management of Technological Innovation course

• Collaborated with local government to evaluate an innovation policy, designed questioners for enterprises and generated a report based on first-hand data analysis• Executed in-depth research and analysis on enterprise innovation strategies to develop legal management and business plans for clients through quantitative patent data analysis• Provided consultations to clients on patentability through patent searching and legal analysis

• Practiced patent searching strategies with USPTO, WIPO, and SIPO database• Conducted quantitative patent data analysis using MS Excel to aggregate multiple reports• Performed data visualization design through pivot table and various dashboard to explain patenting behavioural trends• Participated in data collecting, organizing and interpreting along with research fellows