Entry Level Data Analyst jobs in Canada

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Line of Business: Analytics, Insights, & Artificial Intelligence

Pay Details: $81,600 - $115,200 CAD

TD is committed to providing fair and equitable compensation opportunities. Growth opportunities and skill development are defining features of the colleague experience at TD. The base pay offers may vary based on candidate skills and experience, job-related knowledge, geographic location, and other business needs. As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter for specifics.

The Department Description: The Branch Analytics team within Analytics, Insights and Artificial Intelligence (AI2) provides consultative, data-driven solutions to support operational excellence, regulatory adherence, and performance optimization across TD\'s branch network. The team partners closely with business stakeholders to transform large-scale enterprise data into scalable analytics products, actionable insights, and automated monitoring solutions that directly drive business value.

The Data Scientist II, Branch Analytics will design, build, and deploy advanced analytics solutions across cloud-based platforms, translating complex business problems into production-ready data assets, insights, and automated analytics. This role combines strong technical expertise, analytical thinking, and business partnership to deliver measurable outcomes across operations, risk, and performance management.

• Develop scalable analytics solutions using Python, SQL, and PySpark within cloud environments (Azure Databricks and enterprise data platforms)
• Build curated datasets, automated pipelines, and analytics layers that support operational monitoring, performance insights, and regulatory controls
• Analyze large, complex datasets to identify trends, risks, gaps, and optimization opportunities
• Translate ambiguous business questions into structured analytical frameworks and actionable deliverables
• Embed data quality checks, validation, and automation into all analytics products
• Partner cross-functionally with business stakeholders, data engineering teams, and enterprise analytics groups
• Communicate insights through dashboards, presentations, and executive-ready storytelling
• Continuously improve analytics processes, standards, and reusable data assets
• Support a strong risk and control culture through robust analytical monitoring and governance

• Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance, or computer science).
• Graduate degree preferred or progressive project work experience.
• 3+ years of relevant experience; higher degree education and research tenure can be counted.
• Strong organizational skills with the ability to work in a fast-paced environment and manage multiple deadlines and priorities.
• Ability to effectively work in teams across the bank with multiple stakeholders and to influence and align others.
• Strong risk acumen - challenges the status quo and proactively manages risks.
• Ability to work in ambiguity and simplify complex issues.
• Strong work ethic and ability to execute with speed.

• Proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and PySpark) and SQL (writing complex queries, stored procedures, and data extraction).
• Hands-on experience with machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and causal inference.
• Experience building, training, and deploying machine learning models, including model pipelines, feature engineering, hyperparameter tuning, and model explainability.
• Experience with cloud-based data and AI/ML platforms (e.g., Azure, AWS, or GCP), including deploying and managing models in production environments.
• Proficiency in tools like Power BI, Tableau, or similar platforms to create impactful visualizations and dashboards.

The Workplace Model for this role is "Office Focused"