U

University of Waterloo

Student-run venture capital training fund

Data Analyst

Data ScienceConfirmed live in the last 24 hours
Full-timeWaterloo, ON, Canada$73.7k - $92.1kIn-person

About the Job

Requirements

  • A degree in computer science, statistics, mathematics, data science, economics, or another related discipline is required; an equivalent combination of education and experience may be considered.
  • At least 3 years of experience in work related to data management, data analytics, statistical analyses, and predictive modelling.
  • Proven ability to write SQL queries and use SQL or other tools to extract, transform, and load data for analysis.
  • Proven ability to use R, Python, or equivalent tools for data analysis and visualization.
  • Proven ability to use Python or another scripting language to automate tasks.
  • Knowledge of statistical packages, extract-transform-load methods, and visual analytics.
  • Demonstrated ability to streamline and automate processes.
  • Strong interpersonal, visual, and technical written communication skills.
  • Ability to collaborate effectively with technical and non-technical roles across teams.
  • Strong stakeholder management and prioritization skills.
  • Positions are open to qualified candidates who are legally entitled to work in Canada.

Responsibilities

  • Ensure Faculty data is accurate, consistent, properly maintained, and shared in compliance with privacy protection, confidentiality, and other ethical principles.
  • Identify and address data integrity and reliability issues; use data-cleaning processes to meet data-quality standards and report anomalies and discrepancies to appropriate institutional data stewards.
  • Understand available data, systems, dictionaries, and distribution channels from multiple University information systems and domains.
  • Execute and develop Python scripts that enable data-informed operational processes for Faculty service units.
  • Design and implement dimensional models across multiple subject areas for analytics solutions.
  • Create and maintain documentation as needed.
  • Work independently with varied clients to identify and clarify questions or problems, determine appropriate analytical approaches, and develop effective data solutions.
  • Develop and apply an understanding of University and Faculty policies, procedures, and guidelines, including undergraduate studies regulations, to solution design and analysis.
  • Analyze data using advanced statistical techniques, including regression, clustering, and decision trees, to gain insights.
  • Independently develop and apply forecasting, predictive, and what-if models to address business questions and inform planning, evaluation, and budgeting processes.
  • Assess the appropriateness of machine-learning algorithms and other techniques for business problems and optimize data solutions.
  • Develop reports and data visualizations, including dashboards, graphs, presentations, and web applications, to inform evidence-based decision-making in the Faculty.
  • Maintain Faculty-wide business intelligence reporting, ensuring consistent quality-control practices and current data availability.
  • Develop efficient SQL queries, applying database expertise and sound judgment about business requirements.
  • Provide advice and recommendations based on data analysis, modelling, and interpretation of risks and opportunities.
  • Communicate findings, recommendations, and data through reports, presentations, and visual analytics to support evidence-based decision-making.
  • Research new tools, systems, and practices and recommend improvements across the role's domains.
  • Understand stakeholder-group needs to assess and scope projects and recommend timelines and priorities.
  • Communicate with senior leadership, faculty members, and staff to understand needs, scope projects and terms, update progress, and present findings.
  • Place data and information in proper context by combining University data with qualitative and quantitative environmental or external data and appropriate narrative.

Desired Qualifications

  • Experience with Microsoft Fabric or Power BI.
  • Knowledge of postsecondary education data domains or student data systems.

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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