DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Position Overview:
We are looking for a hands-on QA Manager to lead and scale our Quality Assurance function. This role requires a strong ownership mindset, high execution focus, and the ability to deliver during critical release periods.
You will drive end-to-end quality strategy, improve automation and processes, apply AI to increase efficiency, and build a metrics-driven QA organization. Success in this role means delivering measurable improvements in product quality, release stability, and team productivity.
Key Responsibilities:- Own end-to-end quality strategy across product releases (planning, execution, release readiness).
- Establish and continuously improve QA processes to reduce defects and release risk.
- Lead strong defect management practices (triage, prioritization, root cause analysis, prevention).
- Drive an automation-first approach to increase regression and critical-path coverage.
- Apply AI tools to improve testing efficiency (e.g., test generation, regression optimization, defect clustering, RCA insights).
- Define and track QA KPIs (defect leakage, escaped defects, automation coverage, flake rate, cycle time, release stability) and use data and dashboards to drive measurable improvements.
- Lead, coach, and develop the QA team with clear goals and accountability.
- Collaborate closely with Engineering, Product, DevOps, and Support.
- Ensure QA is involved early in requirement and design discussions and clearly communicate quality risks, status, and release readiness.
Requirements
- 10+ years of QA/testing experience, including 5+ years in a QA leadership role.
- Proven experience building and scaling QA processes across multiple teams or products.
- Strong knowledge of QA methodologies, test planning, defect lifecycle management, and release management.
- Hands-on experience with test automation frameworks and CI/CD integration.
- Demonstrated ownership mindset with strong execution focus, especially during tight release timelines.
- Experience using AI tools or implementing AI-assisted QA workflows.
- Strong experience defining QA metrics, building dashboards, and driving data-based decisions.
- Excellent cross-functional communication and stakeholder management skills.
Benefits
PTO, Stock Option and Health Benefits
Comp Range: CA$100,000 - CA$140,000
