Partner with International Product leadership and market-level Product Development and Product Management teams to transform the function into an AI-native organization, designing the data-product and data agent-context the organization builds on.
Outcome-Driven Product Impact
Own accountability for revenue and growth outcomes across International markets, ensuring modeling, experimentation, and AI investments are prioritized for maximum cross-market impact.
Set the inference and experimentation patterns — designs, guardrails, lifecycle standards — that teams across markets adopt as their default
Frame the questions that change strategy across the organization: define the metric trees and causal levers that multiple business areas and markets manage to, and drive insights that alter org-level roadmaps and investment decisions.
Design the agent-context, evaluation, and delegation-governance architecture the organization adopts — how rigor is encoded, certified, and monitored when analysis runs without a human in the loop.
Capability Building & Craft Elevation
Champion and scale durable Product Data Science capabilities across markets by establishing rigorous standards for inference & algorithms, AI-native evaluation, and data-product / decision governance — your evaluation architectures become the org's pattern.
Set the semantic layers, context, and monitoring patterns that other teams across International adopt as their default.
Mentor top data science talent across regions, fostering ownership, technical excellence, and continuous learning; the framing patterns you set become how the org decomposes problems.
Qualifications
10+ years of experience in Product Data Science, with a demonstrated track record of personally building, shipping, and scaling high-impact models, analytical and experimentation frameworks that drove measurable revenue and growth outcomes across multiple markets.
Master's degree or higher in Statistics, Computer Science, Economics, Applied Mathematics, Machine Learning, or a related quantitative field.
Proven experience transforming data science practices — establishing inference and experimentation patterns, evaluation architectures, and AI-native workflows — that other teams adopt as their default.
Deep technical expertise in SQL and Python, with strong command of causal identification, experiment design, predictive modeling, and AI evaluation (golden datasets, LLM-as-judge, synthetic testbeds) at production scale.
Hands-on experience designing agent-context and delegation-governance architectures — proving which analytical work may run without a human in the loop.
Demonstrated ability to influence senior cross-functional leaders across Product Development, Product Management, and international markets without direct authority.
Familiarity with cross-sell and attach strategies within platform businesses spanning QuickBooks and adjacent products.
Experience operating across international markets (e.g., Canada, UK, Australia) with an understanding of market-specific customer behavior, regulatory, and localization nuances, not required but considered a plus.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Toronto $203,000 - $274,500
