About Équité Association

As a not-for-profit organization, Équité Association supports Canadian insurers to fight fraud by using advanced analytics, intelligence best practices, and coordinated investigations. Combining expert investigative services and advanced analytics, Équité serves as a unified organization, delivering improved service and fraud analytics for vehicle and cargo recovery. Leveraging relationships with law enforcement, partners and industry organizations, Équité serves as a centre point for insurance crime across all insurers, and is protecting Canadians by working to eradicate insurance fraud and crime. Équité, is invested in diminishing crime in Canada, and protecting all Canadians against exploitation.

About the Role

We use a wide range of data and intelligence to achieve four objectives:

1. Help insurers identify fraud through integrated advanced analytics and investigations;
2. Enhance and enable cross-insurer investigations coordinated by Équité;
3. Lead stakeholder in vehicle and hard-asset recover & identification services; and
4. Support law enforcement, regulators, professional colleges and other public investigative agencies to identify criminals and bring them to justice. We will also endeavour to raise public awareness about consumer scams: how they work and how to detect and prevent them.

Reporting to the VP, Chief Data & Technology Officer (CDTO), the Director of Infrastructure & Technology Solutions leads the development and continuous enhancement of the ÉQ Insights analytics platform, including an AWS Data Lake, while expanding the platform’s capabilities to support AI-driven innovation in fraud detection, analytics, and data collaboration. The Director will oversee a technical team of data engineers, software engineers, cloud engineers, and QA specialists, while managing key vendor relationships. This role focuses on infrastructure, data engineering, and platform enablement, ensuring that teams across the organization can successfully develop and deploy AI and data-driven solutions. The role is pivotal in scaling Équité’s data infrastructure, enabling AI experimentation and deployment, and building the foundation for a future-focused innovation roadmap.

Key Responsibilities

• Lead the design and architectural roadmap for the analytics and AI platform using AWS foundational services (VPC, Compute, Storage, Network, Security).
• Deliver and maintain an enterprise-grade platform that supports AI models, machine learning pipelines, and innovation use cases, in partnership with internal teams and external vendors.
• Manage end-to-end analytics delivery: ingestion pipelines, data modeling, dashboards, and analytics workflows with a focus on scalability and readiness for AI use cases.
• Translate AI and data innovation goals into platform capabilities; support POCs for AI/ML models, pilots, and production rollouts.
• Support stakeholder engagement and communication across business units, ensuring transparency and alignment with business priorities.
• Oversee platform operations, including software, cloud infrastructure, and third-party integrations that enable fraud alerting, network link analysis, and advanced analytics.
• Manage intake, prioritization, estimation, and delivery of data requests, while championing data quality and governance practices.
• Support research and exploration of new data sources, technologies, and AI tools to future-proof the platform and strengthen AI enablement.
• Foster a collaborative culture of innovation, partnering with insurers and ecosystem stakeholders to advance industry-wide capabilities.
• Ensure strong collaboration with partners to understand day to day challenges and opportunities to optimize delivery.
• Focus on implementing, scaling, and integrating AI/ML platforms, data pipelines, and APIs. Maintain the infrastructure that supports AI use cases, including deploying fraud detection models into production.
• Oversee the team accountable for data ingestion, orchestration, model deployment, and AI platform reliability.

Ideal Candidate Profile

• University degree in a quantitative discipline (Math/Statistics, Computer Science, Engineering, etc.) or equivalent combination of education and experience.
• Minimum 10 years of experience in analytics, data platforms, or cloud-based technology environments with hands-on exposure to AI/ML projects or platforms.
• Deep knowledge of AWS infrastructure (VPC, Compute, Storage, Network, Security); experience with provisioning tools like CloudFormation or Terraform.
• Proven success in delivering cloud-native platforms and supporting AI-driven products or data science teams.
• Experience managing cross-functional teams (10–15+), including external vendors, engineers, analysts, and IT security.
• Strong technical communication skills and the ability to influence stakeholders at all levels — both technical and non-technical.
• Excellent leadership, planning, and decision-making skills; able to lead within complex and often outsourced environments.
• Comfortable working in fast-paced, innovation-driven teams with a strong focus on outcomes and agility.
• Bonus: Experience integrating AI/ML frameworks, MLOps practices, or open-source tools to support experimentation and deployment.

We encourage applications from all backgrounds and communities. We highly value our diversity and inclusion culture and welcome all candidates, including women, BIPOC, LGBTQ2S+ and allies.