STATISTICS AND ACTUARIAL SCIENCE GRADUATE CO-OP
Want to launch your career faster after grad school? A Graduate Co-op in statistics or actuarial science can get you going. Make professional connections, explore career options, enhance marketable skills and apply your education in the public or private sector. Graduate Co-op full-time work terms can align with your area of academic interest, be available in any semester (not just summer) and allow you to live and work in or outside B.C.
GRAD CO-OP QUICK FACTS
- Before you apply, consult with your academic supervisor about your degree plans and possible integration of work terms
- Apply two terms in advance of your first intended work term (e.g. apply to co-op in Fall to prepare for a Summer work term the following year)
- Complete 1-2 work terms during your degree
- You must finish your work term(s) before completing your academic requirements (e.g. before your thesis defence)
- You’ll maintain your full-time student status while on a work term
- Gain credit for STAT 812 through your work term, click here for details
- Visit the co-op website for upcoming application deadlines
Hear what statistics and actuarial science graduate co-op students have to say…
Acun Demirkaya
Eckler Ltd. (Summer 2026)
Working as a pension actuarial analyst at Eckler has been an incredibly rewarding introduction to the consulting world. My role involves supporting pension consulting work across administration, valuation, and client deliverables. I clean and organize pension data using Excel, assist with administration tasks, and prepare draft reports and presentation materials for clients. I’ve also had the opportunity to learn ProVal to support actuarial valuation work, which has been a personal highlight. It’s been great seeing how what I learned in class actually applies to the real world, and I’m already improving my skills in data analysis, pension consulting, and technical communication.
My advice to other students: Don't be afraid to ask questions early on, especially when learning specialized software or navigating client data. The learning curve can feel steep, but teams are incredibly supportive and want to see you succeed. Also, make sure to start polishing your resume and cover letter with your co-op coordinator well before your search term begins so you can set yourself up for success from day one.
Suhani Daruka
B.C. Cancer Research Institute (Summer 2026)
I am currently working as a biostatistician at the B.C. Cancer Research Institute (Childhood, Adolescent and Young Adult Cancer Survivors (CAYACS) Program), where I support research focused on understanding the educational outcomes of children affected by cancer. A large part of my role involves working with complex health and education data and translating statistical results into meaningful interpretations for researchers and stakeholders. This experience is strengthening both my technical skills in statistical modelling and my understanding of how data-driven research can inform healthcare and education policy in practice.
One of my key takeaways so far is the importance of seeking co-op opportunities that genuinely align with your area of interest. It can be tempting to accept the first opportunity that comes along. My advice to other students is to take time to look for roles that align with what you are genuinely curious about, as that makes the experience much more meaningful and rewarding.
Alana Deng
Leadpages (Summer/Fall 2026)
I am currently working as a Machine Learning Engineer at Leadpages (part of Redbrick, a Canadian technology company headquartered in Victoria, B.C.), an AI-powered landing page builder and conversion marketing platform that helps individuals, creators, entrepreneurs, and businesses build web pages and online experiences to establish their presence and grow online.
As a machine learning engineer, my role is to develop and deploy machine learning and AI systems that enhance product capabilities and support data-driven decision making. My current work focuses on trust and safety applications, including fraud detection and the identification of fraudulent, deceptive, or potentially harmful websites generated through AI-powered website creation tools.
Xuankang (Jacob) Zhu
EA SPORTS (Spring 2026)
During my co-op at EA SPORTS, I worked as a Machine Learning Scientist Intern on real-time generative AI for gameplay. My project focused on improving diffusion-based generation by reducing the number of denoising steps while maintaining visual quality, which involved building teacher-student distillation pipelines, running experiments with action-conditioned video generation, and evaluating performance across different inference settings. A personal highlight was seeing research ideas turn into working demos, especially when connecting machine learning theory with real-time interactive applications.
One piece of advice I would give is to be proactive and curious: ask questions early, document your experiments carefully, and do not be afraid to explore unfamiliar areas. The co-op experience helped me grow both technically and professionally, and it gave me a much clearer picture of how machine learning research is applied in an industry setting.