Data Scientist

Location: North Vancouver

Department: Institutional Research

Position Title: Data Scientist

Working with us

The Institutional Research Department harnesses the power of advanced analytics, comprehensive research, and innovative data solutions to empower our students, leadership, faculty, and staff. Our mission is to provide a clear, data-driven vision that supports the university’s strategic objectives and enhances the overall educational experience.

We partner with departments across the university to ensure data integrity, transparency, and accessibility. Through rigorous research methodologies, we provide critical insights that inform policy decisions, optimize resource allocation, and foster a culture of continuous improvement.

We are constantly exploring new technologies and methodologies to stay ahead in the rapidly evolving field of data analytics and institutional research. Whether it’s predictive modeling, machine learning, or interactive data visualization, we are at the forefront, turning complex data into clear, strategic actions.

Are you ready to delve deep into complex datasets to uncover trends, identify opportunities, and anticipate challenges? Join us in creating a brighter future driven by data!

About the role

Reporting to the Director, Analytics & Institutional Research, the Data Scientist plays a key role in advancing Capilano University’s use of advanced analytics to support evidence-informed decision-making. This position provides specialized expertise in predictive modeling, simulation techniques, and marketing analytics to address institutional priorities in enrollment planning, strategic scenario testing, and student recruitment. The role requires both technical depth and the ability to translate complex analytical outputs into actionable insights for academic, administrative, and marketing leaders.

Working collaboratively, the Data Scientist designs and implements models that forecast student demand, simulate the impacts of strategic decisions, and optimize recruitment strategies. In addition, the position contributes to data engineering initiatives, fosters continuous improvement in analytics practices, and mentors analysts to build institutional capacity.

This is a technically advanced, high-impact role that supports long-term planning, operational efficiency, and the strategic goals of the University.

ILLUSTRATIVE EXAMPLES OF DUTIES

• Design and implement predictive and simulation models aligned with institutional needs.
• Develop and apply simulation models that integrate Human Resources (HR) and financial data to assess the impact of enrollment and program changes, including forecasting staffing levels, instructional costs, and resource allocation.
• Partner with academic, administrative, and marketing teams to translate their questions into advanced analytics and data science solutions.
• Contribute to data engineering efforts, including developing pipelines, supporting cloud migration, and optimizing data architecture.
• Present complex analytical findings through clear, accessible communication tailored to technical and non-technical audiences.

Experience, competencies & qualifications

REQUIRED TRAINING AND EXPERIENCE

• Master’s degree in Data Science, Statistics, Computer Science, Engineering, Operations Research, or a related field.
• Minimum 3 years of experience in a data science or advanced analytics role, with a track record of building predictive or simulation models.
• Experience working with relational databases and writing complex SQL queries.
• Proficiency in Python and/or R and associated data science libraries.

For more information

For more information, please see the complete job description.

Benefits

At Capilano University, we understand that there is more to life than work. That is why we offer comprehensive benefits and support to help you and your family live a balanced life. Take a sneak peak to see what it is like to work at Capilano University.

Salary

The typical salary range for this role falls between $79,731 – $106,308 per annum, commensurate with experience, education, and internal equity, with future opportunities for performance-based pay and career progression.