Ke (Keynes) Xu Email & Phone Number

Vancouver, British Columbia, Canada

• Led the weekly regional financial funding updates and coordinated with other DSS teammates in delivering updates on time
• Streamlined the quarterly performance reporting by utilizing centralized databases and macros throughout the entire reporting process, delivering the reports to the board members and regional teams timely
• Wrote 5,000+ lines of VBA codes, automated monthly routine tasks; macro functions include populating pivot table, importing/exporting data across different sources, interacting with other apps(e.g., outlook and Word).
• Worked closely with the manager on strategic projects and prepared a variety of data analysis write-ups, including changes, patterns, correlations, trends
• Updated the 20-year caseload forecast model (regression models) and highlighted KPI results through PowerBI dashboards
• Examined the impacts of each input as well as the external factors for the 20-year forecasted expenditure model through sensitivity and scenario analysis and provided suggestions on reducing costs effectively.

Richmond, British Columbia, Canada

• Managed the entire month-end bonuses & commissions (B&C) process for over 2800 staff at 28 clubs (UFC, Crunch and Steve Nash), including updating the Excel templates, accruing and finalizing the expenses, and adjusting.
• Forecasted weekly/monthly daily collections and created summarized visuals for the management
• Created both internal and external monthly credit collections reports for the manager to monitor any deviations as well as for credit collection companies to collect members’ latest balances
• Combined data from different sources and generated a list of illegible memberships monthly and coordinated with system admin to remove the accounts
• Assisted FP&A manager in building 2020 P&L budgets for Retail and Tennis Departments (~ $50k)
• Investigated variances of reporting data (KPI, payments related reports) between different sources and avoided a total $10k pay discrepancies

Richmond, British Columbia, Canada

• Print and highlighted all criteria on new agreements’ pricing and promotion (P&P) handouts and checked them one by one after constructing the complex bundles with different agreements, services and price levels to.
• Tested on the sandbox several times before updating the P&P to avoid any potential errors
• Filed all the P&P handouts based on brands and logged them into different categories, speeding up the P&P creation process by 50%
• Checked and responded to Live Agent tickets (operations related inquires) at least twice a day to ensure all issues are resolved promptly
• Screened over 200 deals weekly and provided 24 Operations Managers (OMs) constructive feedback to ensure the validity of the deals
• Compiled weekly and monthly OM performance reports and generated analyses and insights to support Management Strategic decisions

Vancouver, Canada Area

• Worked as a cross-functional analytics team using Agile principles to deliver two major predictive analytics deliverables with R Script, and documented in RMarkdown for reproducibility
• Took an ad hoc approach to learn and apply supervised and unsupervised machine learning methods for fraud detection: - Latent Dirichlet Allocation - Random Forest Model - Extreme Gradient Boosting Model
• Created categories of fraud from unstructured text data using a Mixed Membership approach to Topic Modeling
• Predicted the likelihood of a transaction being audited using Tree Based Ensemble Methods to create two propensity models
• Handled data sets with rare target events using class-imbalance techniques such as Over-sampling, Under-sampling, and Synthetic sampling (SMOTE, ROSE)
• Leveraged Git and Github for R Script and RMarkdown version control

Burnaby

• BUS312 Intro to Finance, BUS336 Data & Decision II, BUS445 Customer Analytics
• Tutored 10+ students in Office and 30+ students in Open Lab on average for each session
• Marked over 300 students’ assignments and exams with high accuracy and completed promptly
• Helped students with their studies by providing useful tips and suggestions

Vancouver, Canada Area

• Handled CAD/USD cash accurately and checked out goods, following strict procedures
• Cooperated with colleagues in closing the store (about 40,000 sq ft) on time
• Received positive feedback in handling customer inquiries and complaints with professional approaches

Master Of Business Analytics

2023 Google Hackathon Challenge - 3rd Place Team Winner 2023 EY Open Science Data Challenge level 1 - 4th Place Team (Canada) 2023 EY Open.

Financial Modeling & Valuation Analyst (Fmva)®

Bachelor Of Business Administration (Honours With Distinction), Finance And Operations Management

Activities and Societies: SFU Business Analytics Hackathon, Linde Davies Investment Challenge, Business Case Competitions• SFU Business.