Top Tech Jobs & Startup Jobs in Toronto

Designs, develops, delivers, and evaluates training and curriculum for internal and external Risk Services customers. Assesses training needs, creates courseware and online help, manages multiple priorities, builds stakeholder relationships, and ensures training solutions align with business objectives.

Lead a team to define and implement enterprise data quality strategies, design and run automated data quality and regression tests, validate end-to-end ETL/ELT pipelines, perform source-to-target reconciliation and data profiling, collaborate with stakeholders, and establish data quality metrics and governance to ensure reliable reporting and analytics.

Provide phone-based support to commercial micro-business clients, handling policy changes, certificates, new business opportunities, and service requests while coordinating with Underwriting, Billing, Risk Services, and Claims. Use multiple systems to deliver accurate, timely, and organized client service in a high-volume, hybrid environment.

Develop and execute integrated content strategies across digital, print, and executive channels. Create thought leadership, award submissions, executive presentations, and campaigns. Partner with senior leaders and cross-functional teams to translate complex ideas into clear, audience-focused messaging while managing multiple projects and maintaining high attention to detail.

Lead regional Risk Services strategy and day-to-day operations; manage staff, hiring, development, and succession; deliver advisory, consulting, training and risk assessments; develop plans, budgets, and priorities; monitor industry trends and support customer safety and business objectives.

Answer billing questions from brokers, agents and clients by phone and email; bill insureds, follow up on past-due premiums, cancel policies, pursue outstanding earned premiums, maintain reports, notify parties of missing bank information, and audit files for discrepancies.

The Data Scientist 2 will engage in the full data science lifecycle, including data extraction, model development, and deployment to meet business needs.

Partner with business, IT, and analytics teams to define and enforce data standards, improve data quality, investigate data issues, and govern large datasets. Use SQL and BI tools and data catalogues to document metadata, shape enterprise-wide governance practices, and influence stakeholders to adopt consistent data management practices.

Design, develop, test, document, and maintain integrations solutions. Collaborate with analysts, architects, engineers, and business stakeholders to align technical and business goals. Support daily operations of integration applications, research and recommend best practices, and keep up to date with company operations and insurance industry trends to improve integration processes.