Toronto, Ontario, Canada
I'm a data and risk leader with 12+ years in fintech and banking, passionate about using AI and analytics to unlock smarter, more inclusive financial products. At Wealthsimple, I helped lead the company’s transformation from a brokerage into a modern retail financial platform, enabling products like credit cards, instant deposits, and margin loans. I built and scaled the credit risk, and market risk modeling programs, and now lead data science across risk, finance, and customer service. Earlier in my career, I spent three years leading credit AI at scale, designing and deploying machine learning systems that have generated tens of millions in revenue while helping more people access credit responsibly. I know what it takes to get models from prototype to production in real-world, regulated environments. What sets me apart is the blend: executive judgment, technical depth, and a strong track record of building teams that deliver.
I was instrumental to Wealthsimple’s transition into a comprehensive retail banking platform -- leading credit, fraud modeling, and market risk, and advising on product, policy, strategy, and financial forecasting. My work helped unlock products like credit cards, instant deposits, and margin loans, and enabled the company’s broader shift into retail banking. My role has grown from 3 staff to 30 and I oversee all risk modeling plus finance and customer service data science. - I was hired to establish a credit risk program. We built Wealthsimple's credit risk program from scratch: models and data that enabled scalable lending and supported products with $100s M in volume. - I advise our risk committee and C-suite leadership on matters of credit and report as necessary. I am one of Wealthsimple's lending officers with authority over lending decisions and I am responsible for maintaining our credit risk policy and governing the credit data supporting our decisions. - I am responsible for fraud models for all channels including application, transactions, account take-over (ATO), withdrawal, onboarding. - I am responsible for market risk data science. The market risk team maintains a market risk data mart and measures risk on brokerage products like margin and options, setting product thresholds, tracking VaR, and building stress scenarios and risk reporting. - I am responsible for customer service data science: CS data, tracking and forecasting of volumes, and optimized routing. - My team is highly collaborative and cross-functional. We are trusted advisors to the product, finance, engineering, operations and customer experience teams.
Finaptic was a banking-as-a-service (BaaS) startup in Toronto. We built a B2B digital banking platform comprising APIs for payments, deposits, lending, risk management and compliance. I was responsible for the lending policy and consumer decisions platform including: underwriting, model monitoring, reporting, and development, plus integrations with vendors including credit bureau and decision engine vendors. Finaptic was acquired by National Bank in Nov 2021.
I'm the director of the Data Science and Machine Learning Innovation team within Retail Credit risk modeling. My team is tasked with developing, promoting and deploying new techniques to enhance retail credit risk decisions. Our innovation comes in the form of software, mathematics, AI & ML, or data. We develop these techniques ourselves or with FinTech partners. I strive to deliver work that is implementable, practical, profitable and scalable to millions of retail customers.
Part of a team founded to enhance credit risk model performance by leveraging: new data sources, fintech partnerships, advancements in statistical analysis and model development methodologies and software, and process enhancements.
Develop models for machine classification of fraudulent transactions - using transaction characteristics, consumer-level marketing data, spatial data, and credit history. Develop strategy for prioritization of fraud mitigation by relative risk.