Sobre esta vaga de Student, Portfolio Analytics (Winter 2027, 4 Months) na OMERS
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 (bonds, swaps and derivatives)
- Deliver the analytic result in simple and convenient visualization
- Work closely with colleagues across Capital Markets, specifically the credit and risk management teams
Preferred Skills & Experience:
- Enrolled in an undergraduate or graduate degree program in computer science, math or business
- Strong academic track record combined with extra-curricular experience
- Strong programming skills, with experience in Python preferred
- Intermediate financial modeling skills (regression and numerical solution of differential equations)
- A creative and enquiring mind
- Good communication skills, team working ability and integrity
- Html/SQL experience is an asset
This posting is for an existing vacancy.
The expected salary range for this position is $66,300.00 - $87,750.00 per year, prorated based on the term of the contract.
You may also be eligible to receive an annual Incentive Award pursuant to our Short-term Incentive plan and our Long-Term Incentive plan (if applicable), and to participate in our group benefits and retirement plans – details on these elements of compensation are included within OMERS & Oxford offer letters.
As one of Canada’s largest defined benefit pension plans, our people-first culture is at its best when our workforce reflects the communities where we live and work — and the members we proudly serve.
From hire to retire, we are an equal opportunity employer committed to an inclusive, barrier-free recruitment and selection process that extends all the way through your employee experience. This sense of belonging and connection is cultivated up, down and across our global organization thanks to our vast network of Employee Resource Groups with executive leader sponsorship, our Purpose@Work committee and employee recognition programs.
Artificial intelligence (AI) tools are used to support certain stages of the OMERS recruitment process. While AI assists us in our process, human judgment and decision-making remain central to our candidate experience.
