• Continue building data foundation across People domains (performance, departures, workforce planning, payroll, etc.). • Drive data literacy and data-informed mindset among our diverse People stakeholders. • Generate actionable insights - we want cohesive, meaningful analysis rather than standard metrics without purpose. • Create insight-driven dashboards that clearly communicate business progress and are intuitive to use (no design background needed, just effective data visualisation). • Make complex data simple by building data models that make diverse sources accessible and easy to work with. • Strengthen data governance across People Org and improve data quality through best practices implementation. • Partner with analytics engineers to streamline data flow from warehouse to downstream reporting, enabling more effective team collaboration. • Enable stakeholder success by working closely together to tackle immediate business challenges.

• Leading a team of ~25 data scientists and analytics engineers across Marketing Data • Acting as a strategic partner to Marketing, Growth and Finance teams • Driving best in class global marketing measurement strategies including next-gen attribution models and marketing mix modelling • Implementing AI and ML powered marketing solutions for campaign optimisation and customer experience • Translating our ambitious marketing plan and our crazy big goals for the Canva brand into scalable data infrastructure and actionable insights • Collaborating with stakeholders and operational partners to refine reporting formats and rhythms to provide the most value for the lowest lift • Shaping the future of data’s role in marketing through experimentation, storytelling, and strategic influence

• Uses best practices and traditional statistical/modeling techniques to develop and maintain rating, economic and other models as necessary and in consideration of the business goals of the model • Provide tools, educate and support state teams in the implementation of models and other decision-making support • Follows appropriate analyses to be conducted for projects to make recommendations to achieve corporate goals • With minimal direction plans, implements, manages, and/or contributes on projects that are up to moderate complexity and are small-to moderate scale using accepted project management standards • Forecasts short-term and long-term deliverables with assistance • Tracks own plan performance and project timeline and communicates and presents project status • Ensures project controls are in place throughout the lifecycle of the project within own tasks • Supports the development/ design of new plans, programs, processes, products up to moderate complexity • Assists in the development of communication strategies and materials to support new plans, programs, processes, products; solicits input from stakeholders • Participates in the evaluation of procedures and processes regularly and makes observations or suggests improvements • Contributes to market share growth and profitability by recommending changes to products, pricing, risk management • Understands standard market specific implications of business strategies • Assures proper execution of regulatory/legislative practices for Product Management • Understands and follows internal and external compliance requirements/standards • Trains/coaches team members or peers and actively shares expertise with peers

• Architect and implement generative AI and Agentic solutions using LLMs, diffusion models, and other cutting-edge techniques for text, image, and multimodal generation • Develop custom fine-tuning and prompt engineering strategies for foundation models to meet domain-specific needs • Explore innovative applications of generative AI in areas such as conversational agents, automated content creation, and citizen engagement platforms • Build scalable pipelines for model training, evaluation, and deployment on cloud and edge environments • Collaborate with product and engineering teams to embed generative AI capabilities into enterprise platforms • Conduct research and experimentation with emerging architectures (e.g., transformers, diffusion models, VAEs, GANs) to stay ahead of industry trends • Establish best practices for responsible AI, including bias mitigation, explainability, and ethical use of generative models • Communicate complex AI concepts to executives and non-technical stakeholders in a clear, actionable manner • Mentor junior data scientists and contribute to frameworks, tools, and reusable components for generative AI development.