Actuarial Specialist – Claims Analytics

TD•Montreal, QC

2d•$110,600 - $160,000•Onsite

About The Position

Actuarial expert accountable for the soundness of data, methodology, models, and analytical assumptions while delivering priority claims operations initiatives end‑to‑end — from current‑state journey mapping to future‑state rewired design, value‑at‑stake sizing, and deployment of AI models into claims workflows. This role partners with Claims Operations, Product, and Technology to enhance workflows, build standalone tooling where required, and establish controls for safe, scalable adoption. Provide technical leadership within Claims Analytics and contribute to enterprise analytics standards where relevant.

Requirements

Demonstrated ability to translate advanced analytics into deployed decision support within Claims operations (workflow integration, adoption, monitoring).
Understands the industry, competition and the factors that differentiate the organization.
Integrates knowledge of the enterprise sub-function’s or business line’s overarching strategy in developing solutions across multiple functions or operations.
Acts as a technical expert / lead integrating cross-function understanding within their own field of specialty; may manage team(s) of related specialists.
Leads cross-functional teams or projects with significant resource requirements, risk and / or complexity.
Uses sophisticated analytical thought to exercise judgement and identify solutions.
Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
Graduate's degree preferred with either progressive project work experience or 8+ years of related experience.
Fellowship actuarial level is preferred.

Responsibilities

Develops the communication, interpretation, application and implementation of actuarial analysis and results to the business.
Ensure the availability and quality of data used for all actuarial analysis, based on a thorough knowledge of the data systems.
Own end‑to‑end analytical deliverables for claims operations initiatives.
Develop and operationalize predictive and GenAI use cases across the claims lifecycle, including monitoring/measurement of performance and adoption, to improve advisor efficiency and customer experience.
Use a wide range of programing languages (e.g. Python, R) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract insights from the big data.
Visualize insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
Analytical thought leadership and stay current on developments in data mining and the application of data science.
Develop and enhance functional procedures including review for actuarial soundness.
Establish model controls, monitoring, and meaningful human‑in‑the‑loop decision points to reduce automation bias and ensure appropriate oversight.
Support risk mitigation and control design for AI use cases in Claims, including operational guardrails and exception handling.
Support implementation of best practices, risk mitigation, risk controls as well as process, policy and procedures for the actuarial/modeling function.
Maintain a culture of risk management and control, supported by effective processes in alignment with risk appetite.
Quantify value at stake and benefits (productivity, cycle time, leakage, accuracy) and track realized outcomes for deployed use cases.
Participate in cross-functional / enterprise / initiatives as a subject matter expert helping to identify risk / provide guidance for complex situations.
Conduct internal and external research projects; support the development/ delivery of presentations / communications to management or broader audience.
Lead cross-functional delivery squads (Claims Ops SMEs, Product, Tech, Data) to drive from analysis to pilot to scaled implementation.
Provide day‑to‑day technical guidance to actuarial analysts / data scientists on model design, validation, and integration readiness.
Participate fully as a member of the team, support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensures timely communication of issues/points of interest.
Keep current on emerging trends/ developments and grow knowledge of the business, related tools and techniques.
May supervise other team members / actuarial professionals and/or provide day-to-day work directions where appropriate.
Contribute to team development of skills and capabilities through mentorship of others, by sharing knowledge and experiences and leveraging best practices.
Lead, motivate and develop relationships with internal and external business partners / stakeholders to develop productive working relationships.
Contribute to a fair, positive and equitable environment that supports a diverse workforce.