Actuarial Modeling & Technical Manager Job Toronto area,Ontario Canada,Finance & Banking

Description:

Remote type:
Hybrid/Remote

Locations:
Flexible, but preferably in US/Canada (New York, Chicago, Montreal)

Time type:
Full time

Company Overview:

The Actuarial Consulting Practice of Oliver Wyman advises clients across a broad spectrum of risk management issues. We are a rapidly growing practice with offices across the globe. Our actuaries hold the highest professional qualifications and are recognized as experts in their field(s). We use mathematical and statistical modeling skills and our qualitative assessment methodologies to assist clients in evaluating and addressing risk.

Our solutions help clients manage and prepare for the potential financial consequences of uncertain future events. We bring a combination of broad-based expertise with specialized knowledge of specific risks, allowing us to provide independent, objective advice in the three primary areas of risk: healthcare, life and annuity, and property and casualty. 

The Property and Casualty Consulting Practice assists insurance companies, self-insured corporations, government entities, and other organizations with all aspects of managing property and casualty insurance exposures. We guide P&C clients on their qualitative assessment and quantification of risk and loss exposures, and offer advice on a range of issues, from external business strategy and internal risk management to economic capital modeling and new product development.

Summary:

Oliver Wyman’s US P&C Actuarial Consulting Practice is hiring an Actuarial
Modeling & Technical Lead to join our Actuarial Modeling, Analytics & Transformation team. The role focuses on hands-on development, validation, and operationalization of actuarial models and workflows, understanding actuarial & business requirements and converting those into production ready code and tools. The Actuarial Modeling & Technical Lead will partner closely with engineering to deliver auditable, reproducible actuarial solutions. Candidates should combine strong P&C actuarial experience with practical software skills, and an appetite for AI-enabled development.

The role requires deep hands-on actuarial modeling experience in pricing, underwriting, claims and/or reserving (model building, rater build, actuarial process improvement, accelerators and tool builds, etc.)

Responsibilities:

Build, test, document, and maintain actuarial logic implemented in code (Python/R) or modeling platforms, ensuring reproducible, version-controlled workflows.

Design and implement end-to-end actuarial workflows across pricing, reserving, underwriting, and claims analytics; create developer-ready specifications and technical documentation.

Leverage AI-assisted development tools, cloud platforms and machine learning algorithms to improve modeling, code generation, automated testing, and documentation while maintaining actuarial governance and correctness.

Perform exploratory data analysis, validate data pipelines (SQL, Databricks, Azure), and turn complex datasets into clear recommendations with client-ready reporting, dashboards & relevant visualizations.

Act as the liaison between actuarial subject matter experts and engineering teams: translate actuarial specifications into technical requirements, review implementations, and validate via unit and integration tests.

Contribute to practice tooling, best practices, and business development; represent the practice at industry events.

Qualifications:

Actuarial credentials (e.g., FCAS/FIA/ACAS) or active progress toward a recognized actuarial qualification.

3+ years of P&C actuarial experience in consulting or insurance with hands‑on work in pricing, reserving, or claims analytics.

Demonstrated experience in P&C modeling, building predictive models (e.g. regression type, GLM/GMB-type, advanced machine learning models, ect.) for frequency/severity, loss cost, and other relevant actuarial use cases.

Strong technical skills with actuarial tools and experience with Python, R, or SQL are advantageous. Experience with Git/Git Hub and Databricks preferred.

Familiarity with cloud ML and data platforms (Azure ML) and ML Ops practices a plus.

Experience with visualization tools (Power BI,…


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