Currently working on SimGym (Cut down A/B testing time, or get alternative to running A/B tests by using AI agents mimicking a merchant's actual buyer to provide feedback on online storefront changes). Check it out here https://www.shopify.com/editions/winter2026#online

Previous accomplishments:

1. Built an LLM pipeline that analyzes merchant theme codes and generates recommendations for conversion improvement and assessment of code changes.

2. Helped with the launch and data-driven iterations of Shopify Bundles, increased variant limits (highly requested merchant feature), Catalogs (now part of Markets) in Merchandising.

3. Led the data team for Custom Storefronts (Hydrogen, Headless, Shopify Web Components) including the onboarding of multi-million dollar GMV merchants who adopted Shopify's "headless" solutions.

4. Significantly improved the time-to-connect of 3rd Party Domains to Shopify, enabling merchants to onboard to Shopify faster through data analytics and A/B testing on enhancements to domain flows.

5. Improved Product Marketing analytics by building a strong analytics pipeline and reporting on Shopify Editions.

6. Automated metric anomaly detection and growth accounting to automate data science tasks, leading to 20% less full time employee time needed to support a domain.

7. Owner of Shopify's data team's pair programming loop.

Data Science manager leading the finance decision team to support Shopify's Finance and Executive team. Here are some work I had done, categorized by the data science activities.

Data Leadership:

• Scaled up sub-teams to provide data support to Finance, Investor Relations, Compliance, Tax and Legal

• Mentor interns and data scientists

• Shares context from domain knowledge to provide recommendations for teams across Shopify to support new product launches, implement business process changes and using data science to improve labour productivity in Finance

Business Analysis:

• Applied causal inference and econometric techniques for projects where experimentation was not an option.

• Used survival analysis for the revamp of the affiliate payouts.

• Used time-series models to monitor key metrics for anomalies. Some anomalies that were detected led to changes in business process improvements.

• Scenario analysis for Covid-19 as an input for financial planing.

• Flag unusual drivers of revenues and costs across various product lines to drive profit margins favorably.

• Created tools to decompose metrics by segments to provide timely insight to country managers or product owners to follow up on events of interest.

Data storytelling:

• Support Investor Relations and the Financial Planning and Analysis in preparation for Earnings Call and Board Meetings.

• Used IRS Data to understand drivers of Gross Merchandise Volume growth during the economic lock-down.

ETL and Data Service Levels:

• Ships code to model business processes in the form of Kimball-Style dimensional models.

• Ensures that data models owned by the team is meeting both service level agreements (in terms of freshness), and is up to date with the evolution of Shopify's business.