Data Analyst Intern, Data & AI Enablement (Fall/September 2025, 8+ Months)

Internship List•Oakville, ON

9h•Hybrid

About The Position

Geotab is seeking a Data Analyst Intern who will work to help utilize vast datasets to draw meaningful insights and solve business problems. This internship position will analyze and mine business data to identify correlations and discover patterns from various data points. If you love technology, and are keen to join an industry leader - we would love to hear from you! As a 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.

Requirements

Pursuing a Degree in Computer Science, Math, Software Engineering or a related field.
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).

Nice To Haves

Technical experience using SQL, Python or Google BigQuery is an asset.
Some knowledge of data mining/data warehousing, data modeling, statistical analysis, database management, reporting, and data analysis.
Experience with developing machine learning models and in feature engineering is an asset.
Some knowledge of data visualization tools (e.g. Superset, Tableau).

Responsibilities

Assist with the design and maintenance of data systems and databases using statistical tools to interpret data sets.
Collaborate with colleagues from the Data and Analytics team plus other functions of the business to drive results.
Build and review statistical, predictive and machine learning models to drive sourcing accuracy.
Ensure data quality throughout all stages including data sourcing/collection, generation, normalization, and transformation.
Engage in automotive engineering 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.