Data Analytics, Summer 2025 - Toronto (Co-OP/Internship) - 8 Months

We are committed to providing our Co-ops/Interns with a student experience that provides a supportive and engaging learning environment while developing skills and business acumen. Students will have the opportunity to participate in a variety of experiences including our Corporate Speaker Series, Fireside Chats, Volunteer opportunities and Networking events.

Eligibility Note: To qualify for a student (Co-op/Internship) opportunity, students must be enrolled in their academic studies at a post-secondary institution (university/college) and must be returning to school after completion of their work term with QuadReal. If you are a student registered in an official co-op program at your post-secondary institution and completion of a final work term is a mandatory component for you to graduate, you are eligible to apply with the understanding that you will leave QuadReal at the end of your work term or have the possibility to be considered for full-time opportunities.

Based in Toronto, the Data Analytics Intern will be an integral member of our team, contributing to the development and deployment of data-driven insights to enhance research, property investments, etc. including multifamily properties, student apartments, storage facilities and other real estate sectors. Working closely with cross-functional teams in analytics, engineering, and business intelligence, you will support the data analysis, the creation of predictive models, optimization frameworks, and advanced visualizations to guide strategic decision-making.

Join our dynamic and innovative Data Analytics team, committed to propelling organizational growth through data-driven insights. We collaborate cross-functionally to tackle complex business and product challenges, continually striving to enhance our offerings and strategies.

What We Offer:

• An organization and leaders that support your development through meaningful work experience

• A Student Mentorship Program designed to provide 1:1 support throughout your experience

• Opportunities to build your industry knowledge through Corporate Speaker Series & Fireside Chats

• Giving back to community with your peers and team members through volunteering events

• Opportunities to build long lasting industry and professional relationships

What You Will Experience:

• Opportunity to innovate and contribute to high-impact projects, gaining deep experience in both location-based technology such as visualization and decision making using machine learning or other artificial intelligence systems.

• Collaborate with teams to develop advanced analytics models and machine learning algorithms for location intelligence related analytics, building predictive model for climate risks applied to real estate properties, valuation, rental demand, optimizing property operations, and identifying investment opportunities, etc.

• Analyze large-scale datasets from various sources, including census data, point of interest data, property management systems, market data, and geospatial information, to uncover actionable insights.

• Contribute to the exploration and integration of external data sources, such as points of interest and census data to enhance predictive capabilities.

• Participate in the end-to-end development lifecycle of data science projects, including problem formulation, data preparation, modeling, and deployment.

• Collaborate with mentors to solve complex real-world problems in multifamily property investments using cutting-edge data science techniques

What You Will Bring:

• Currently pursuing a degree in a relevant field (e.g., Data Science, Statistics, Computer Science, Geography, Geomatics, or related discipline).

• Strong analytical and problem-solving skills, with hands-on experience in statistical modeling and machine learning frameworks using Python (e.g., pandas, scikit-learn, TensorFlow) or R (e.g., tidyverse, caret).

• Experience with Python for data manipulation (e.g., NumPy, GeoPandas) and modeling, SQL for complex database querying, and proficiency in Azure cloud services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks).

• Familiarity with cloud platforms such as AWS (e.g., S3, Lambda) or GCP (e.g., BigQuery, Vertex AI) is an asset, though Azure is our primary environment.

• Familiarity with geospatial data analytics and related tools:

• PostGIS for spatial querying and analysis within PostgreSQL.

• GIS software such as QGIS or ArcGIS for visualization and spatial data processing.

• Interactive mapping tools like Kepler.gl and Carto for advanced geospatial visualization and insights.

• Proficiency in collaborating with cross-functional teams (e.g., data engineering, product managers, and designers) to translate complex data requirements into practical solutions.

• Strong communication skills, both written and verbal, to explain complex technical concepts to non-technical stakeholders.

• A passion for learning and working with new data technologies, with the ability to adapt quickly in a fast-paced environment.

• Familiarity with version control (e.g., Git) and experience using dashboards or BI tools (e.g., Tableau, Power BI) is a plus.