Design and build automated dashboards and pipelines to monitor fraud performance end-to-end (intake → detection → investigation → outcome)
Develop self-serve analytics tools to empower Fraud Operations and business partners
Contribute to the automation of fraud reporting and workflows (e.g., reducing manual processes, improving data timeliness)
Perform deep-dive exploratory analyses to identify fraud patterns, emerging risks, and operational gaps
Translate complex findings into clear, actionable recommendations that influence fraud strategy and business rules
Evaluate the performance and impact of fraud initiatives (e.g., detection models, business rules, awareness tactics)
Act as a thought partner to Fraud and Underwriting operations translating business problems into analytical solutions
Act as an AI enabler, embedding artificial intelligence into day-to-day fraud analytics processes
Ensure data quality and integrity through validation, documentation, and continuous improvement of data processes
Advance data literacy across the team, promoting best practices in business intelligence and data storytelling
Mentor and support team growth, sharing technical knowledge and business insight to uplift team capability.

Bachelor's or Master’s degree in Actuarial science, Mathematics, Statistics, Business Intelligence, Data Science, Computer Science, Finance, or a related field
2-7 years of experience in analytics, data analysis, and statistical analysis
Experience in the general insurance industry
Experience with fraud detection, anomaly identification, or risk analytics frameworks
Bilingual in English and French (required)
Strong coding skills in SQL and Python
Experience with data visualization tools (e.g., Power BI, Tableau, or Shiny/Posit)
Excellent analytical skills and attention to detail, especially for quality control and data validation
Skilled in critical thinking, creative problem-solving, and time management

Actuarial Analyst II

Key skills