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University of Waterloo

Student-run venture capital training fund

Data Analyst and Evaluation Specialist

Data Analysis +1Confirmed live in the last 24 hours
Full-timeWaterloo, ON, Canada$73.7k - $92.1k

About the Job

Requirements

  • A bachelor's degree in business, statistics, economics, or data analytics, or a combination of equivalent experience and education.
  • At least 3 years of experience in a data analysis and/or research role working with complex datasets.
  • A strong educational and professional background in data management, statistical analysis, associated computer applications, program evaluation, and applied social research methods using qualitative and quantitative methods.
  • Experience manipulating, transforming, and visualizing data with Python and/or R.
  • Experience creating and maintaining reports and dashboards in Power BI using various data connections.
  • Experience working with relational databases and creating queries in SQL.
  • Advanced knowledge of Excel, including functions and formulas, pivot tables, Power Query, and macros.
  • Experience developing surveys for data collection and performing data analysis.
  • A record of and commitment to ongoing learning and engagement in equity, diversity, inclusion, anti-racism, accessibility, and indigenization, and the ability to connect this learning to assessment, evaluation, and data analysis practices.
  • Demonstrated leadership and guidance in using descriptive and inferential statistics to understand trends, patterns, and dependencies related to strategic issues.
  • Knowledge of barriers to student success for underrepresented or non-traditional students and students who are academically at risk, and of how these barriers can affect data collection techniques and program evaluation practices.
  • A strong understanding of assessment and evaluation processes, including instrument design.
  • Strong knowledge of data management, manipulation, interpretation, and analysis using statistical analysis or data transformation tools including Excel, SQL, Python, and/or R, and knowledge of reporting and data visualization tools such as Tableau or Power BI.
  • Ability to create clear and precise process documentation.
  • Experience working within collaborative and document management environments such as Microsoft Teams and SharePoint.
  • Ability to deliver timely, accurate, comprehensible, professional-quality data analytical reports.
  • Organizational skills and the ability to handle multiple tasks and meet deadlines amid changing priorities.
  • Consultation and communication skills, including the ability to explain analysis results to non-technical audiences such as university administrators and campus stakeholders.
  • Ability to use descriptive and inferential statistics to analyze data and knowledge of data-gathering methodologies, including surveys, interviews, focus groups, community forums, literature reviews, environmental scans, situational analysis, and needs assessment.
  • Ability to work independently and as part of a team.
  • Working knowledge of generative AI concepts and applications in data analytics, reporting, and higher-education decision support, including data readiness, ethical considerations, privacy implications, and limitations.

Responsibilities

  • Operate within University policies and best practices for privacy, confidentiality, and records and information management, and advise internal stakeholders on data and records management practices.
  • Create and maintain documentation to support best practices and business continuity.
  • Develop a deep understanding of data, systems, dictionaries, and distribution channels across university information systems; lead discovery and requirements gathering with departmental teams and technical system owners to identify data sources, workflows, system constraints, reporting needs, and evaluation requirements.
  • Apply data quality standards and identify data anomalies and discrepancies for resolution by institutional data stewards.
  • Explore tools, systems, and practices and recommend improvements to data flow, automation, and information analysis.
  • Apply descriptive and inferential statistics to analyze trends, patterns, and dependencies in strategic and operational issues.
  • Collaborate with partners, including academic support units and faculties, to improve and automate data reporting and dissemination, including Power BI dashboards.
  • Consult with Institutional Analysis and Planning, Information Systems and Technology, and other departments on the design, implementation, testing, and operation of computer systems for collecting, storing, reporting, and analyzing student-success data and trends.
  • Follow guidance from Institutional Analysis and Planning on sensitive or restricted data management, and collaborate with Institutional Analysis and Planning, Information Systems and Technology, the Registrar, and faculty analysts on data initiatives to reduce duplicated effort.
  • Educate self and others about how bias, privilege, and discrimination can affect data collection and interpretation.
  • Develop Power BI dashboards, visualizations, reports, and analytical products for real-time monitoring, strategic planning, operational decision making, accountability reporting, portfolio-level insights, and articulation of the student experience.
  • Create reusable analytical frameworks and data extracts for ongoing departmental reporting cycles and continuous improvement.
  • Collaborate with teams to interpret findings, refine reporting products, validate insights, and ensure usability for varied stakeholders.
  • Support analysis of large institutional student surveys with Institutional Analysis and Planning, Marketing and Undergraduate Recruitment, faculties, and other departments, and develop complementary inquiries to inform departmental and university responses; recommend how university-level data informs departmental strategic direction.
  • Clean, merge, and format large complex datasets to support student programming and service delivery.
  • Prioritize and respond to ad hoc and routine data inquiries.
  • Use an equity- and anti-racist-informed approach to qualitative and quantitative data collection, interpretation, and dissemination.
  • Work with department heads, faculties, and other clients to identify and clarify questions or problems and provide effective data responses.
  • Support development of program outcomes, assessment plans, and indicators.
  • Analyze trends and patterns over time using benchmarks and comparative data.
  • Provide strategic direction to management and leadership teams in creating and maintaining outcomes-based evaluation plans, data-gathering methods, tools, analysis, and use of results for strategic direction and decision making.
  • Provide training and competency-building opportunities to staff to support a culture of evidence.
  • Support and advise leadership on research strategies, opportunities, results, analyses, priorities, and long-range planning.
  • Lead efforts to ensure departmental data practices are equity-informed.
  • Collaborate with counterparts in Institutional Analysis and Planning on initiatives including survey management and interpretation, forecasting, retention definitions and analyses, and participation in large-scale surveys such as the National Survey of Student Engagement; contribute departmental progress and outcome indicators to institutional accountability measures, including those related to the university strategic plan.
  • Lead data analytics projects across the Associate Provost, Students portfolio and campus-wide or faculty-specific areas, including advanced and complex research, collection, organization, and analysis of data and information.
  • Provide evidence-based direction on key performance indicators for areas across the department.
  • Advise and inform the department about plans, features, and results of Institutional Analysis and Planning or other department- or faculty-related studies and data that may affect student success.
  • Build constructive relationships to support business process and data-related collaboration with university partners, including the Registrar's Office, Institutional Analysis and Planning, Marketing and Undergraduate Recruitment, Graduate Studies and Postdoctoral Affairs, and faculty leadership.
  • Serve on committees and working groups, contribute data and analytical expertise, and foster information sharing and collaboration on projects.
  • Lead teams without direct supervisor responsibilities.
  • Participate in departmental events and administrative responsibilities, including orientation and convocation, and other duties as assigned.
  • Provide coaching, training, and co-op student development to support student growth and development.

Desired Qualifications

  • Experience establishing data connections using APIs.
  • Experience within an educational setting.
  • Experience developing assessment and evaluation processes and continuous-improvement plans or approaches for large- and small-scale programs and initiatives.
  • Experience using Qualtrics.
  • Experience with data governance and privacy.

About the Company

University of Waterloo

Student-run venture capital training fund

The University of Waterloo’s Student Venture Fund (SVF) gives students hands-on training in venture capital by evaluating startups, conducting market research, valuing companies, doing due diligence, and making investment recommendations under faculty and industry supervision. Students perform the full investment process and manage a live portfolio of early-stage investments with guidance from mentors. Unlike typical courses, SVF provides real-money, end-to-end learning with a supervised portfolio that blends classroom rigor with practical investment experience. The goal is to train students in venture-capital skills while building real-world investment experience and strengthening connections with the startup and investment community.

Company size
11-50
Company stage
Not listed
Total funding
$3.4M
Headquarters
Waterloo, Canada
Founded
2017

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