Senior Data Scientist - Security

About the role

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 a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point. Where and how you can work Our flagship campus is in Sydney. We also have a campus in Melbourne and co-working spaces in Brisbane, Perth and Adelaide. But you have choice in where and how you work. That means if you want to do your thing in the office (if you're near one), at home or a bit of both, it's up to you. What you'd be doing in this role As Canva scales change continues to be part of our DNA. But we like to think that's all part of the fun. So this will give you the flavour of the type of things you'll be working on when you start, but this will likely evolve. You'll be a senior data scientist in an embedded analytics team within Canva's Security group. We solve hard data problems across security: building analytical models, maintaining backend services, and giving leadership the numbers they need to make decisions. Your work will span three areas: 1. Security metrics that drive decisions You'll own the metrics that tell Security leadership how we're actually doing. That means building and maintaining scorecards and KPIs across areas like vulnerability management, identity & access, and compliance. You'll design data models, build dashboards, define OKRs with security leads, and translate what the data says into clear recommendations. The goal isn't just reporting - it's influencing where the team invests next. 2. Evaluations and quality for AI-powered services We're building AI-powered services to solve security problems at scale. You'll own the evaluation framework - curating ground truth datasets, designing quality metrics, building human feedback loops, and iterating on classification approaches. You'll need to think like both a data scientist and a product owner here. 3. Analytical solutions for real-time security problems Security at Canva's scale generates problems that traditional data warehousing can't solve alone. Think streaming analytics over petabytes of logs, high-concurrency queries for near-real-time threat detection, and monitoring access patterns across multiple cloud environments. You'll partner with security engineers and privacy teams to scope these problems, evaluate the right architectures, and build the analytical foundations to solve them. Day to day, you'll be: Analysing security datasets to find patterns, measure risk, and surface insights that change how teams prioritise Designing experiments, building statistical models, and stress-testing assumptions Writing SQL, Python, and data models to turn raw security data into something stakeholders can act on Presenting findings to security leads, engineering leaders, and senior stakeholders Collaborating across security, privacy, compliance, and data platform teams Mentoring peer Data Scientists, running knowledge-sharing sessions, and contributing reusable patterns and frameworks that raise the bar beyond your immediate team. You're probably a match if You've got a track record of turning data into decisions - not just delivering dashboards, but actually changing what a team does next. Ideally, you've done this in a security or risk context, but strong analytical experience in other domains works too. You'll need: Strong SQL and Python skills, and real experience with modern data stack tools like dbt and cloud data warehouses (not just "familiar with" - you've built and maintained production models) The ability to own a problem end-to-end: scoping what to measure, building the data models, validating the output, and communicating what it means to people who aren't technical Experience designing evaluation frameworks or quality metrics for ML/AI systems - things like ground truth curation, precision/recall analysis, and feedback loops Clear, concise communication skills - you'll be writing docs, presenting to leadership, and explaining complex findings in plain language Comfort working independently in a small team as a senior individual contributor - you'll need to self-direct and proactively flag what matters It'd be great if you also have: Experience in the security domain - data classification, access control, vulnerability management, compliance frameworks, or threat detection Familiarity with LLMs in applied settings (prompt engineering, RAG, evaluation methodology) Experience with dimensional modelling, semantic layers, or building self-serve analytics infrastructure Exposure to streaming or real-time analytics architectures A background in maths/statistics and a degree in a STEM area Naturally share what you've learned - whether that's mentoring teammates, presenting at guild or specialty forums, or writing documentation that helps others level up. Experience at a tech company and familiarity with how modern data teams operate About

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