Graduate co-op scientist at TD, a global financial institution, developing machine learning models and analytics solutions. Querying data, engineering features, and translating insights into banking decisions.
Responsibilities
Interpret data, produce insights, create relevant collateral/data visualization reports, and recommend actions on complex issues
Perform Python/SQL data queries and support datasets for analysis/modeling
Clean data and perform feature engineering using best practices
Analyze large, spatially enabled datasets and identify trends and insights to inform business decisions
Communicate findings to technical and non-technical audiences
Support team members and business partners in developing, testing, and deploying machine learning models
Work on forecasting, optimization, or classification/regression models
Proactively identify and solve business problems and opportunities suited to data-driven solutions
Develop proposals and approaches
Collaborate with business partners on analytics-solution business cases
Requirements
Currently enrolled in a recognized graduate degree in Computer Science, Mathematics, Engineering, Science, Statistics, Business, Data Analytics, Business/Commerce, or a related field
Must intend to return to school at the start of the work term
Strong statistical and analytical skills and interest
Strong proficiency in Python, SQL, or other data-related programming languages
Strong proficiency in Object-Oriented Programming
Knowledge of spatially enabled data and geospatial processing tools/platforms
Knowledge of Azure, R, AWS, Databricks, and/or GitHub is a plus
Excellent verbal and written communication
Ability to work collaboratively and effectively in a team environment
Applications must include a transcript, cover letter of one letter-sized page or less, and a resume of maximum 2 pages
Must reside in Canada, where the role is located
Benefits
World class training
Interactive sessions with key leaders across TD
Learning sessions focused on innovation, personal branding, and professional and personal growth
Supportive community of students and professionals
Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs
Regular career, development, and performance conversations
Online learning platform
Mentoring programs
Training and onboarding sessions
Accessibility accommodations for recruitment and interview processes
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Senior Machine Learning Engineer building conversational AI agents and production ML systems. Helping Numa automate automotive dealership service and sales through evaluation - first tooling and infrastructure.
Senior ML Engineer building production ML, RAG, and agentic AI capabilities for SailPoint’s cloud identity security platform. Driving scalable, customer - focused AI solutions from research to production.
Senior ML Engineer developing debiased pCTR and conversion models for Instacart’s grocery advertising ecosystem. Advancing ranking, retrieval, and sequence modeling across ads surfaces.
Senior AI/ML Engineer building Generative AI, RAG, and agentic solutions for pharmaceutical Statistical Programming. Deploying secure, validated, production - ready AI applications with Python and AWS.
Senior Machine Learning Engineer building LLM - powered lab interpretation and clinical decision - support tools for Fullscript’s healthcare platform. Owning AI systems from prototyping through production.
Staff ML engineer building models, evaluations, and agentic systems for Sourcegraph’s code - understanding products. Improving enterprise code search quality, latency, cost, and reliability.