Duration

• 12 month work-term beginning May 2026.

The Position

As a Revenue Operations Data Analyst Intern your key area of responsibility will be to assist with the design and maintenance of data systems and databases using statistical tools to interpret data sets. On a typical day, you will work closely with your direct supervisor, other interns in the same department, as well as other teams within the business. The successful candidate will be an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and others.

Responsibilities

• Collaborating with colleagues from the Revenue Operations Data Analytics & Insights team plus other functions of the business to drive results.
• Ensure data quality throughout all stages including data sourcing/collection, generation, normalization, and transformation.
• Engage in revenue generation research projects as requested by the supervisor.
• Promote data-driven decision-making across the team, using tools such as SQL, and Google Sheets.
• Provide leaders with insight in order to make data decisions to provide the most consistent and usable data for all teams across the company.

Requirements

• Degree in Computer Science, Engineering, Mathematics, or a related field of study in progress.
• Some experience as a Data Analyst or pursuing a career path in Data Analytics/Data Science.
• Technical experience using SQL, Python or Google BigQuery is required.
• Knowledge of data mining/data warehousing, data modeling, statistical analysis, database management, reporting, and data analysis.
• Familiarity with Large Language Models (e.g., Gemini), with an interest in applying them to analyze unstructured data like sales notes and customer feedback.
• A curiosity for using AI agents and agentic workflows to automate RevOps tasks like data quality checks, lead routing, or reporting.
• Experience with developing machine learning models and in feature engineering is an asset.
• Some knowledge of data visualization tools (e.g. Superset, Tableau).
• Strong communication, organization, analytical, and time management skills, as well as a willingness to learn and a strong work ethic.
• Technical competence using software programs, including but not limited to, Google Suite for business (Sheets, Docs, Slides).

Company