Senior Data Scientist; Global Security

Job Description

As a Senior Data Scientist on our Security Insights and AI team, you will contribute to building RBC's next-generation intelligent defense systems. You will design and deploy advanced machine learning solutions that anticipate and detect digital and cyber threats. Leveraging cutting‑edge AI techniques, statistical modeling, and large-scale data analytics, you'll work to deliver enterprise‑grade threat detection systems that automate complex security operations, accelerate our defensive readiness, and set new standards for digital protection and organizational resilience.

• Work closely with stakeholders to understand their needs and build solutions using advanced machine learning methods in the domains of fraud, cybersecurity, and data privacy.
• Design and implement end‑to‑end data pipelines: from data cleaning to model development to writing production level code.
• Implement supervised and unsupervised machine learning models, data mining methods, statistical analysis, and pipelines to prepare and integrate various data types and sources.
• Quickly learn new methods, big data tools and technologies presented in research communities to implement and adapt within our data products and models.
• Collaborate proactively with various business and operation units to design innovative solutions to optimize processes and deploy production‑scale solutions.
• Work on challenging and research‑based initiatives using advanced machine learning methods focusing on tangible outcomes.

• At least an undergraduate degree (PhD or Masters preferred) in a quantitative field (Engineering, Statistics, Mathematics, Computer Science, Economics, Sociology, Psychology etc.).
• 2-5 years of experience with advanced programming skills (Python, PySpark) and experience in developing machine learning models using supervised and unsupervised approaches; experience with data preprocessing, feature and representation learning, anomaly/outlier detection.
• Strong data sense, critical thinking, and technical documentation skills.
• A passion for simplifying and automating work, making things better, continuous learning, solving open‑ended problems, improving efficiency, and helping others.
• Strong communication skills with ability to work cross‑functionally to articulate, measure and solve issues.

• Previous experience in cybersecurity/fraud domains.
• Experience with MLOps to build end‑to‑end pipeline and deploying models in production.
• Experience with graph analytics.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
• Leaders who support your development through coaching and managing opportunities.
• Ability to make a difference and lasting impact.
• Work in a dynamic, collaborative, progressive, and high‑performing team.
• A world‑class training program in financial services.
• Opportunities to do challenging work.

• Address: 16 YORK ST: TORONTO
• City:
  Toronto
• Country:
  Canada
• Work hours/week: 37.5
• Employment Type:
  
  Full time
• Platform: TECHNOLOGY AND OPERATIONS
• Job Type: Regular
• Pay Type:
  
  Salaried
• Posted Date:
• Final date to receive applications: