If building models that help people make better decisions, understanding uncertainty, and turning complex systems into meaningful predictions sounds like your kind of challenge, we're looking for you. As an Architecture Research Intern, you'll use simulation and queueing theory to understand how business changes (new service channels, process redesigns, demand shifts) ripple through operations and shape the customer experience. From forecasting wait times to modelling the dynamics of complex operational systems, you'll help develop solutions that improve experiences for our members. Either way, you'll apply your research skills to real-world problems where uncertainty isn't a complication, it's part of the solution. ~ Together, we help protect the things that matter most to our more than one-million members—everything from roadside safety to retail savings, food security to childhood well-being. And with operations that span automotive, registries, travel, insurance, and more, the opportunities to grow with us are almost limitless Building on a century of proud service in Alberta communities, we're passionate about making a meaningful difference in the places where we live and work. Competitive wage Employee-exclusive discounts on travel, insurance, memberships, and more Vacation earnings paid out with each pay period Flexible work models that makes sense for your lifestyle You're comfortable working with incomplete information and building models that help make sense of it. You communicate technical concepts clearly and can explain uncertainty without creating confusion.



You love turning research ideas into practical models that create measurable value. Apply queueing theory to model customer flow, congestion, and waiting (for example multi-server queues, priority queues, queues with abandonment and retrials, and queueing networks) and use it to derive rapid, interpretable wait-time estimates. Build simulation models (discrete-event, agent-based, and/or system dynamics) to evaluate how proposed business changes affect wait times, service levels, abandonment, and overall customer experience before they are implemented. Compare analytical queueing results against detailed simulation and real operational data to determine where theory holds, where it breaks down, and which approach best suits each decision. Formulate and analyze continuous-time models of system behavior using ordinary and stochastic differential equations (for example fluid and diffusion approximations of queues, including heavy-traffic limits based on reflected Brownian motion), and validate them against detailed simulation and real operational data. Design, test, and refine models that capture uncertainty, customer behavior, and system dynamics. Apply probabilistic and statistical techniques to evaluate performance, calibrate and validate models,



and improve predictive accuracy. Run scenario, sensitivity, and what-if analyses that help business leaders understand bottlenecks, trade-offs, and future outcomes. You're currently pursuing, or have completed, an MSc or PhD in Mathematics, Applied Mathematics, Physics, Statistics, Operations Research, Computational Science, or a closely related quantitative discipline. You have in-depth knowledge and hands-on experience of queueing theory, including Markovian and general queues (M/M/c, M/G/1, G/G/c), Little's Law, queues with abandonment and priorities, queueing networks, transient and steady-state analysis, and heavy-traffic and diffusion approximations. You can fit queueing models to real data and judge when their assumptions hold. You have a strong foundation in differential equations (ordinary, partial, and/or stochastic), including Brownian motion and diffusion processes, Fokker-Planck equations, and numerical methods for SDEs, and can apply them to model the dynamics of real systems. You have working knowledge of optimization, particularly time-constrained or real-time settings: simulation optimization, stochastic and dynamic programming, metaheuristics, or anytime algorithms. You have a strong foundation in probability and stochastic processes, with experience in one or more of the following: You're proficient in Python and can independently translate models and research concepts into reliable, well-tested code (for example NumScript, SciPy, SimPy, and optimization libraries). Remote

📌 Architecture Research Intern (Canada)
🏢 AMA - Alberta Motor Association
📍 Canada