Applied ML Scientist Co‑op — Winter Term

TD; Toronto; Hybrid; CAD 46,000 - 74,000; Part time

Job summary

TD is offering a Winter-term 4-month co-op/internship in Toronto focused on analytics and AI. You will interpret data, produce insights, and create visual reports to support business decisions.

The role emphasizes Python/SQL data queries, feature engineering, and collaboration with partners to deploy ML models. The program targets students pursuing a graduate degree in CS, Math, Engineering, or related fields, with strong statistical and analytical skills and a willingness to return to school

Qualifications

• Enrolled in a graduate degree and plan to return to school at term start.
• Strong statistical and analytical skills are required.
• Proficiency in Python and SQL, plus object-oriented programming.
• Knowledge of spatial data and geospatial tools is preferred.
• Experience with cloud platforms (Azure/AWS) and collaboration tools is a plus.

Responsibilities

• Interpret data and produce insights to support business needs.
• Perform Python/SQL data queries and prepare datasets for analysis and modelling.
• Support development and deployment of machine learning models (forecasting/optimisation/classification).
• Identify business problems and propose data-driven solutions.
• Collaborate with partners to develop analytics solutions and business cases.

Skills

Python

SQL

Object-Oriented Programming

Data analytics

Geospatial data

Communication

Education

Graduate degree in Computer Science/Math/Engineering/Statistics/Data Analytics

Tools

Azure

AWS

Databricks

Github

Job description

TD is offering a Winter-term 4-month co-op/internship in Toronto focused on analytics and AI. You will interpret data, produce insights, and create visual reports to support business decisions.

The role emphasizes Python/SQL data queries, feature engineering, and collaboration with partners to deploy ML models. The program targets students pursuing a graduate degree in CS, Math, Engineering, or related fields, with strong statistical and analytical skills and a willingness to return to school