Senior Data Scientist - Security

Canva Canva · Enterprise · Melbourne, Australia · Information Technology

Senior Data Scientist role focused on security analytics, building metrics, evaluation frameworks for AI services, and real-time security solutions. Requires strong SQL/Python, experience with data stacks, and designing ML/AI evaluation metrics. Familiarity with LLMs and streaming analytics is a plus.

What you'd actually do

  1. 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. 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. 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.

Skills

Required

  • Strong SQL and Python skills
  • modern data stack tools like dbt and cloud data warehouses
  • built and maintained production models
  • 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
  • ground truth curation
  • precision/recall analysis
  • feedback loops
  • Clear, concise communication skills
  • writing docs
  • presenting to leadership
  • explaining complex findings in plain language
  • Comfort working independently in a small team as a senior individual contributor
  • self-direct
  • proactively flag what matters

Nice to 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

What the JD emphasized

  • building and maintaining production models
  • Experience designing evaluation frameworks or quality metrics for ML/AI systems
  • ground truth curation
  • precision/recall analysis
  • feedback loops

Other signals

  • building analytical models
  • building and maintaining scorecards and KPIs
  • design data models
  • build dashboards
  • translate what the data says into clear recommendations
  • influencing where the team invests next
  • own the evaluation framework
  • curating ground truth datasets
  • designing quality metrics
  • building human feedback loops
  • iterating on classification approaches
  • think like both a data scientist and a product owner
  • streaming analytics over petabytes of logs
  • high-concurrency queries for near-real-time threat detection
  • monitoring access patterns across multiple cloud environments
  • partner with security engineers and privacy teams
  • evaluate the right architectures
  • build the analytical foundations
  • Analysing security datasets to find patterns, measure risk, and surface insights
  • Designing experiments, building statistical models, and stress-testing assumptions
  • Writing SQL, Python, and data models
  • 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
  • contributing reusable patterns and frameworks
  • turning data into decisions
  • changing what a team does next
  • strong analytical experience
  • Strong SQL and Python skills
  • modern data stack tools like dbt and cloud data warehouses
  • built and maintained production models
  • own a problem end-to-end
  • scoping what to measure
  • building the data models
  • validating the output
  • communicating what it means
  • Experience designing evaluation frameworks or quality metrics for ML/AI systems
  • ground truth curation
  • precision/recall analysis
  • feedback loops
  • Clear, concise communication skills
  • writing docs
  • presenting to leadership
  • explaining complex findings in plain language
  • Comfort working independently in a small team
  • senior individual contributor
  • self-direct
  • proactively flag what matters
  • Experience in the security domain
  • data classification
  • access control
  • vulnerability management
  • compliance frameworks
  • threat detection
  • Familiarity with LLMs in applied settings
  • prompt engineering
  • RAG
  • evaluation methodology
  • Experience with dimensional modelling
  • semantic layers
  • building self-serve analytics infrastructure
  • Exposure to streaming or real-time analytics architectures
  • A background in maths/statistics
  • a degree in a STEM area
  • Naturally share what you've learned
  • mentoring teammates
  • presenting at guild or specialty forums
  • writing documentation that helps others level up
  • Experience at a tech company
  • familiarity with how modern data teams operate
  • empower the world to design
  • insightful data scientists
  • help us make that happen
  • product has grown enormously
  • 100s of millions of users
  • generating enormous quantities of data
  • fuel our future growth
  • better understand our data
  • self-motivated individuals
  • curious about our product and our users
  • excited to seek out valuable insights
  • act as a genuine data partner
  • LOT of data
  • make the most of it
  • Security Insights team
  • agile team
  • critical mission
  • scaling our data ana