Lead Data Scientist - Experience Value (Growth) - ANZ Remote

📋 Description

• • Own the end-to-end data strategy for Canva’s logged-in experience, translating billions of user events into clear, actionable growth levers that directly influence onboarding, activation, retention, and resurrection KPIs.
• • Lead, mentor, and grow a distributed team of 4-6 embedded data scientists, setting the bar for analytical rigour, experimentation excellence, and compelling storytelling that turns complex datasets into product decisions.
• • Define and steward the north-star metrics for onboarding, personalisation, and lifecycle journeys—partnering with Product, Engineering, and Design to ensure every roadmap item is measurable, testable, and tied to user value.
• • Architect and run large-scale A/B and multivariate experiments from hypothesis generation through power analysis, implementation review, statistical testing, and post-launch measurement, shipping recommendations that move the needle for 170M+ monthly active users.
• • Build and evolve self-serve BI foundations in Snowflake, Looker, and Canva’s internal experimentation platform so that PMs, designers, and marketers can answer their own questions without sacrificing statistical rigour.
• • Translate raw event streams into predictive models and next-best-action frameworks that deliver hyper-personalised experiences across onboarding checklists, trigger-based emails, in-product nudges, and B2B sales prioritisation.
• • Champion a culture of data-driven decision making by running workshops, writing internal playbooks, and creating reusable SQL & Python libraries that raise the analytical IQ of the entire Logged-in Experience group.
• • Collaborate with Data Engineering to improve data quality, instrumentation, and latency—ensuring that every experiment and dashboard rests on trustworthy, real-time data.
• • Present findings to C-level stakeholders, distilling weeks of analysis into crisp narratives backed by clear visuals, confidence intervals, and concrete next steps.
• • Stay ahead of industry trends in growth analytics, causal inference, and machine-learning-powered personalisation—experimenting with new techniques and scaling the ones that prove ROI.
• • Balance speed and rigour in a fast-moving scale-up: shipping scrappy analyses to unblock sprint decisions while also investing in long-term analytical infrastructure that compounds team productivity.
• • Foster psychological safety and inclusive leadership, ensuring every team member—regardless of background—can do the best work of their career while influencing one of the world’s most loved design platforms.