

Global real estate investment, development and management firm with $89B AUM across multiple regions.
Interns will liaise with portfolio, asset, investment, development, accounting, and operations teams to gather data for quarterly valuation updates, analyze operating budgets and financial statements, create and update stabilized cash‑flow models, and assess inputs such as rent rolls, operating and capital expenses, and leasing assumptions. They will also assist in internal and external appraisal processes, prepare valuation summaries and meeting minutes, review third‑party appraisal reports, and lead a special project to develop a comprehensive database and visualisation tools for stakeholders.
Candidates should be currently enrolled in a program such as Real Estate, Finance, Mathematics/Statistics, Computer Science, or Economics, with a strong quantitative and analytical skill set, detail‑orientation, and advanced proficiency in Excel, PowerPoint, and Word; knowledge of Argus Enterprise and business intelligence tools is a plus. Working toward a CFA or AACI designation, prior experience in real‑estate firms, and a genuine interest in a real‑estate career are also valued.
The company offers students a supportive learning experience that includes a Speaker Series, Fireside Chats, volunteer opportunities, and networking events. To qualify, candidates must be enrolled in a post‑secondary institution, be returning to school after the term, and be part of an official co‑op program where the work term is required for graduation.
QuadReal provides meaningful work experience, a Student Mentorship Program with one‑on‑one support, access to corporate speaker events, case competitions that foster cross‑functional collaboration, and community‑focused volunteering events, all designed to help interns build lasting industry relationships.
The role pays an hourly rate of $28, with total compensation determined by skill, experience, education, market factors, and internal equity. QuadReal values diverse experiences and perspectives, uses AI‑assisted screening alongside human review, and encourages applicants whose qualifications may not perfectly match the posting to apply.