Associate Director, Data Science - School of Medicine bei Simon Fraser University

Who We Are

Simon Fraser University is a leading research university, advancing an inclusive and sustainable future. Our purpose – the essence of SFU – is to create and connect knowledge, learning and community for deeper understanding and meaningful impact. We are committed to fostering excellence, innovation, belonging and community in all that we do.

Help build B.C.’s new medical school from the ground up!

At the SFU School of Medicine (School), we envision a medical education system where students and residents learn as part of a team in primary care and other community-level settings, in patient-centred environments, and with a curriculum that considers social, environmental and prevention contexts. As we establish the school in Surrey, B.C., our growing relationships with the local community, Fraser Health Authority, First Nations Health Authority, physicians and Indigenous partners will help us to meet the diverse health needs of the communities we serve and improve access to primary care throughout the province.  We seek to advance reconciliation by embedding and equalizing Indigenous knowledge systems in our learning, research and practices while resting on a solid foundation of high-quality, accredited education and world-class research efforts that keep us oriented towards measurable socially accountable outcomes.

The Assessment, Evaluation & Accreditation (AEA) Office supports the School of Medicine by developing integrated, evidence-informed systems that strengthen learner assessment, program evaluation, and accreditation. The team designs scalable data structures, dashboards, and analytic tools that enable real-time insights and support continuous quality improvement across programs. Working closely with faculty, academic leaders, and medical education technology partners, the AEA Office advances SFU’s commitment to innovation, excellence, and inclusive learning environments. Our team culture is analytical, collaborative, and learner-centred, grounded in integrity, reflective practice, and respect. We value curiosity, service, creativity, and data-informed approaches to strengthening medical education.

About the Role

The Associate Director, Data Science leads the development of AI-enhanced data systems that power learner assessment, program evaluation, and accreditation within the School of Medicine. This role designs scalable data engines, predictive models, and dashboards that provide actionable insights to strengthen academic success. Working collaboratively with faculty, technology teams, and administrative partners, the role advances analytics frameworks that identify learner needs, support curriculum development, and guide continuous quality improvement efforts. Upcoming initiatives include enhancing predictive modelling capacity, expanding NLP-supported analysis of narrative assessment data, refining accreditation-readiness dashboards, and implementing responsible AI governance. This position supports SFU’s commitment to evidence-based decision-making, innovation, and high-quality medical education while building capacity across the institution to interpret and apply data effectively.

The ideal candidate is a collaborative and innovative data science leader who combines technical depth with excellent communication skills. They excel in AI/ML modelling, statistical analysis, data architecture, and transforming complex datasets into clear insights for diverse audiences. Grounded in integrity, professionalism, and inclusive practice, they build strong relationships and mentor team members in emerging technologies. They are adaptable, solutions-focused, and skilled at planning and prioritizing within evolving environments. They embody SFU’s core competencies, demonstrating creativity, sound judgment, emotional intelligence, and a people-centred approach to supporting learner success and continuous quality improvement.

Full Job Description 

Qualifications

Master’s degree in Computer Science, Mathematics, Statistics or an AI/ML focused field and three years of experience in applied statistics, data science, or quantitative research, or an equivalent combination of education, training and experience.

• Expertise in advanced statistical analysis and AI/ML-driven predictive modelling.
• Demonstrated ability to design and maintain scalable data engines and analytics frameworks.
• Strong skills in data visualization using Power BI, Tableau, and related tools.
• Ability to translate complex data into clear, actionable insights for non-technical audiences.
• Strong interpersonal communication and collaboration skills.

What We Offer

At SFU, our goal is to ensure our people are valued and supported by promoting a healthy work-life balance, professional growth and development, as well as a safe and respectful workplace. We offer continuing employees who belong in the Administrative & Professional Staff Association (APSA):

• 4 weeks’ vacation (prorated for the first year)*
• Hybrid-work program for eligible positions
• Employer paid defined benefit pension plan
• On-campus tuition waiver for employees and their immediate family members*
• Off-campus tuition reimbursements and professional development funds*
• And more! View our benefits brochure

*Prorated for part-time employees

Additional Information

Please include your cover letter and resume in one attachment.

SFU is an equity employer and strongly encourages applications from all qualified individuals including women, Indigenous Peoples, visible minorities, people of all sexual orientations and gender identities, persons with disabilities, and others who may contribute to the further diversification of the university.

We are committed to ensuring that the application and interview process is accessible to all applicants. If you require any assistance or accommodations, please contact [email protected].