Welcome to My Personal Website

Hello, I'm Lu Cheng

About Me

Welcome to my personal website. I'm Lu Cheng, a Senior Manager and Lead Model Developer with 8+ years of experience in developing and validating predictive models across credit/fraud risk, user behavior, customer growth, and market risk domains. I'm passionate about data science and applying statistical and machine learning techniques to solve real-world problems.

I'm open to relocation and am a Canadian Citizen.

Contact: chenglu0310@gmail.com | (1)647-549-0449

Education

University of Waterloo

Graduated: April 2022

PhD in Statistics

Thesis Research: Large-scale complex feature selection and inference

Award: "Top 1" in PhD Stage I Comprehensive Examination (written exam on six core statistical courses)

University of Waterloo

Graduated: May 2010

Master in Statistics (with Co-op)

Beijing Normal University

Graduated: July 2008

B.S. in Statistics

Professional Experience

Senior Manager (Lead Model Developer) at Bank of Nova Scotia

June 2022 - Present

Spearheaded the development of customer analytics and insights strategy, and commercial rating models with End-to-End Modeling Leadership.

  • Designed and implemented the bank's first-generation first-party fraud detection models for Caribbean credit card and unsecured loan portfolios, achieving 10x to 50x lift in fraud identification.
  • Redesigned and migrated the bank's comprehensive Caribbean portfolio review dashboards from Tableau to Power BI.
  • Led data-driven strategy design to enhance risk-reward predictions, customer segmentation, credit limits assignment, and risk-based pricing.
  • Redeveloped multiple credit rating models using machine learning techniques such as Random Forest and XGBoost, optimizing model weights using rank-based correlations and genetic algorithms.

Award: Honored with the "Best of Best 2023" performance award for outstanding contributions.

Senior Data Scientist at Deloitte

July 2018 - June 2022

Worked on diverse projects in User Behavior Prediction, Credit Risk and Market Risk Models.

  • Developed first-generation advanced attrition and points redemption models for credit cards, leveraging discrete event-history modeling and feature engineering.
  • Developed Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models for regulatory compliance (IFRS 9).
  • Audited several retail portfolio credit risk rating models, assessing their validity and regulatory compliance.
  • Validated pricing models for bond futures, interest rate futures, interest rate swaps and risk rating models for asset-backed securities.

Model Validation Specialist at Bank of Montreal

November 2016 - June 2018

  • Validated multiple retail product stress testing models (including PD, LGD, EAD, PPNR, and fair lending).
  • Led the validation of a pioneering Credit Card PD model built using an account-level hazard rate methodology.
  • Contributed to the development of model monitoring frameworks; designed metrics (KPI) and established thresholds.

Biostatistician at Princess Margaret Hospital

May 2010 - August 2011

  • Applied dimensionality reduction algorithms to perform feature selection on data with extremely low signal-to-noise ratios.
  • Built diagnostic and predictive time-to-event survival analysis models on head and neck cancer patients.

Statistical Analyst (Co-op Intern) at University of Alberta

May 2009 - December 2009

  • Applied cluster-effect-adjusted non-parametric tests and longitudinal data modeling to identify risk factors.
  • Performed time series analysis and built multiple regression models for various medical research projects.

Skills

Technical Skills

Domain Expertise

Key Projects

Fraud Detection Models

Designed and implemented first-generation first-party fraud detection models for Caribbean credit card and unsecured loan portfolios, achieving 10x to 50x lift in fraud identification through model-generated alerts.

Credit Card Attrition & Points Redemption Models

Developed advanced attrition and points redemption models leveraging discrete event-history modeling and feature engineering to analyze millions of features from multiple sources.

Credit Rating Models

Redeveloped credit rating models for business borrowers, improving model performance using machine learning techniques and optimizing model weights using rank-based correlations and genetic algorithms.

Contact

Email: chenglu0310@gmail.com

Phone: (1)647-549-0449

Open to relocation | Canadian Citizen