Student, Portfolio Analytics (Winter 2027, 4 Months)

OMERS
Toronto, Ontario, CanadaPosted Sep 7, 2026
Finance / Investment BankingWinter 2027

About the role

Choose a workplace that empowers your impact. Join a global workplace where employees thrive. One that embraces diversity of thought, expertise and experience. A place where you can personalize your employee journey to be — and deliver — your best. We are a purpose-driven, dynamic and sustainable pension plan. An industry leading global investor with teams in Toronto to London, New York, Singapore, Sydney and other major cities across North America and Europe. We embody the values of our 665,000 members, placing their best interests at the heart of everything we do. Join us to accelerate your growth & development, prioritize wellness, build connections, and support the communities where we live and work. Don’t just work anywhere — come build tomorrow together with us. Know someone at OMERS or Oxford Properties? Great! If you're referred, have them submit your name through Workday first. Then, watch for a unique link in your email to apply. Are you ready to unleash your potential and join a high-performing team of investment professionals who value hard work, fun and camaraderie? As a Student Analyst, Portfolio Analytics, at OMERS Capital Markets, you will be part of a team of investment professionals that are building a world-class portfolio analytics platform. If you are passionate about data management and analytics and enjoy working with large amounts of data, we want to hear from you!

At OMERS, you can expect

  • Collaboration with colleagues and leaders who offer diverse experiences and expertise in a supportive environment
  • The opportunity to develop and grow your investment expertise while being a part of an engaged team of investors committed to meeting the pension promise
  • Ongoing learning, mentorship and networking opportunities

You will be responsible for

  • Develop and implement quantitative analytical tools involving large amounts of data from a wide spectrum of data types
  • Develop tools to help mathematically model an array of security types (bond

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