Predictive Enrolment Analytics Lead
Competition 1346
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Description
This position is a part of the Association of the Academic Staff of the University of Alberta (AASUA).
In accordance with the Administrative and Professional Officer Agreement, this full-time continuing position offers a comprehensive benefits package found on our Benefits Overview page and an annual salary range of $71,557 to $119,269.
Location - This role is hybrid with a mix of remote and in-person work at North Campus Edmonton.
Working at the University of Alberta
The University of Alberta acknowledges that we are located on Treaty 6 territory, and respects the histories, languages and cultures of First Nations, Métis, Inuit and all FirstPeoples of Canada, whose presence continues to enrich our vibrant community.
The University of Alberta is a community of knowledge seekers, change makers and world shapers who lead with purpose each and every day. We are home to over 14,000 faculty and staff, more than 40,000 students and a growing community of 300,000 alumni worldwide.
Your work will have a meaningful influence on a fascinating cross-section of people — from our students and community members, to our renowned researchers and innovators, making discoveries and generating solutions that make the world healthier, safer, stronger and more just. Learn more.
Working for Enrolment Research, Analytics and Insights
Enrolment Research, Analytics and Insights (ERAI) unit at the Registrar's Office is responsible for operational data reporting and fowrard-looking research on a averiety of topics related to university enrolment. The unit collaborates with stakeholder groups to deliver high quality of data products and strategic insights to support senior leadership in evidence-informed decision-making.
Position
Under the overall direction of the Assistant Registrar, Enrolment Research, Analytics (ERAI) and Insights, the Predictive Enrolment Analytics Lead is a key member of the ERAI unit. The position requires a high degree of independence, detail orientation, communication skills, system thinking skills and superior expertise in quantitative analytics. The position has a focus on developing and implementing advanced data models through machine learning and statistical approaches, with the intention to build unit capacity in predictive and prescriptive analytics. One of the first projects will be to build a robust model to predict enrolment which will provide insights to University administrators for strategic planning. The work also involves communicating ideas and outcomes to seek stakeholder buy-in and recommend solutions to address specific operational or strategic questions. Developing and maintaining a strong network of analytics is also essential for this position to stay current on best practices and resources, and to establish unit/RO branding on advanced analytics inside and outside of the University.
Duties
Insights and leadership support
- Supports the development and communication of strategic plans for advanced enrolment data analytics and machine learning initiatives, ensuring alignment with University's vision, strategies, policies, and plans.
- Supports defining and creating the oversight and governance of advanced enrolment analytics and machine learning solutions with a focus on innovation, resilience, performance, scalability and simplicity.
- Provides insights to develop and initiate potential enrolment research opportunities that are inspired and guided by machine learning operations and outcomes.
- Provides technical support and insight to the University’s Integrated Enrolment Growth Plan.
- Provides technical support and guidance to other analysts at ERAI.
- Initiates and supervises professional projects (related to machine learning modeling and advanced analytics that need support from other unit Analysts) and takes accountability to the entire process.
Strategic and technical expert
- Leads, facilitates and coordinates the execution of ERAI's technical vision on advanced enrolment analytics and machine learning.
- Leads the exploration and transformation to evolve the unit/department's analytical capacity from descriptive to predictive and prescriptive.
- Develops and champions advanced enrolment analytics and machine learning principles and processes at various levels, identifying opportunities for transformational improvement.
- Leads the establishment of a systemic mechanism of ERAI’s advanced enrolment data analytics including processes, tools, platform, resources, data, and products.
- Develops an environmental scan product that summarizes best practices in business intelligence in post-secondary enrolment management.
- Closely works with external contractors, other departments/units, and faculties to develop, implement, and deliver machine learning solutions to predict enrolment-related activities at different levels.
- Collaborates with ERAI's Programmer Analysts and stakeholders to develop robust automation solutions to improve work efficiency and reduce manual input.
- Engages in continuous learning and professional development to stay updated on industry trends, emerging technologies, and best practices in data analytics and business intelligence.
Relationship management
- Promotes advanced analytics and machine learning tools/outcomes to other departments/units and faculties to be one of the main factors of decision-making for senior leadership.
- Supports the establishment of strong relationships with stakeholders, gaining buy-in for initiatives and fostering collaboration across departments/units and faculties.
- Makes an effort to establish a research network with the government, other institutions, and the analytical industry to share outcomes, ideas and resources of advanced analytics.
Qualifications
- A post-secondary degree from a recognized institution in Computer Science, Statistics, Mathematics, or a related discipline. Bachelor’s degree or equivalent is required, Master/PhD degree is an asset, equivalent combinations of education and experience will be considered.
- 5+ years of experience in progressively responsible roles within business intelligence, advanced data analysis, and machine learning.
- 3+ years of experience in leading advanced analytics projects or teams.
- Strong knowledge of conducting scientific research.
- Strong knowledge of data science and statistical principles.
- Advanced skills in data extraction, manipulation and analysis.
- Excellent programming skills in R, Python, and/or SAS.
- A proven record of successfully managing complex projects and delivering impactful business outcomes.
- Have a strong mindset and skills to implement technical change at the institutional level, from vision to realization, through collaboration with business stakeholders.
- Experience in collaborating with cross-functional teams and senior leadership to translate business needs into data strategies and initiatives.
- Extensive experience in business analysis and problem-solving to transform complex business problems into conceptualized research questions and then into data-driving solutions.
- Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders and influence decision-making.
- Have extensive experience in business analysis and problem-solving to transform complex business problems into conceptualized research questions and then into data-driving solutions.
Interviews are expected to take place in mid-to-late October.
At the University of Alberta, we are committed to creating an inclusive and accessible hiring process for all candidates. If you require accommodations to participate in the interview process, please let us know at the time of booking your interview and we will make every effort to accommodate your needs.
We thank all applicants for their interest; however, only those individuals selected for an interview will be contacted.
The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.
ApplyNote: This opportunity will be available until midnight September 12, 2024, Edmonton, Alberta local time.