Staff Data Scientist - Discovery

Canva
Sydney,Posted 31 March 2026

Tech Stack

Job Description

Join the team redefining how the world experiences design. Hey, g'day, mabuhay, kia ora, 你好, hallo, vítejte! Thanks for stopping by. We know job hunting can be time consuming, so we’ll get straight to the point. Where and how you can work Our flagship campus is in Sydney, with spaces across Australia. You have the flexibility to choose how and where you work best. What you'd be doing in this role This role sits within the Content & Discovery Supergroup, in the Discovery Group, where we’re building a highly personalised Canva - helping users discover over 100M+ templates, photos, videos and elements. As a Staff Data Scientist, you’ll operate as a senior individual contributor with end-to-end ownership of ambiguous, high-impact problem spaces. You’ll shape product strategy through data, influence decision-making across the group, and elevate the standard of data science across Discovery. Your primary goal will be to uncover product opportunities that help users succeed in their goals and to influence product strategy across Discovery — both by demonstrating their potential impact and by raising the standard of how data science is done in the group.  At the moment, this role is focused on Data insights: Your main goal in Discovery is to drive cross-group strategic insight — synthesising signals from user behaviour data into a coherent point of view that shapes product direction. You'll set the standard for how the group turns data into decisions, and empower teams across Discovery to make informed choices that delight customers. Raising the floor: Uplifting the team's baseline impact by identifying and fixing what slows us down — improving practices, automating low-value and busy work, and building self-serve tooling that makes better use of everyone's time. If there's leverage being left on the table, you'll help the team pick it up. Raising the ceiling: Setting direction and advancing the DS craft and influence within Discovery — connecting the dots across specialties and the company to drive customer value, leading by example, and helping others grow. You'll define what great data science looks like in our group and create the conditions for the team to consistently punch above its weight. Building Relationships: Engaging with and influencing stakeholders across the group and the company to align on strategy and surface opportunities. Facilitating open dialogue across teams, helping others build the relationships they need to succeed, and modelling the kind of cross-functional collaboration that drives results at scale. Experimenting: Designing and leading experiments to test hypotheses formulated from user research and your own strategic insights, analysing the results, and using them to influence next steps. You'll also help raise the group's experimentation standard — sharing knowledge, improving shared practices, and championing rigour across teams. Influencing with Metrics: Designing and building goal metrics at a group level, forecasting and setting targets, designing analytics events that track feature usage, and building frameworks and dashboards that others can build on. Then using them to diagnose issues and shape what the business does — at a group and company level. You're probably a match if You have proven record of influencing business and product decisions with data and directly contributing to company growth. You thrive in tackling ambiguous and undefined problems by gathering context, exploring data, and paving the way step by step, onboarding the stakeholders along the way. You have the soft skills & personal qualities to understand the various stories user behaviour data might tell and to influence decision makers: balancing speed and accuracy, identifying biases in interpreting data, connecting the dots between different research, speaking persuasively in public, and writing concisely and clearly. You have a strong base in the fundamental technical skills of data science – hyp ... (truncated, view full listing at source)
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