Full Stack Data Science Engineer

Full Stack Data Science Engineer building scalable AI/ML models, dashboards, and data solutions. Supporting analytics-driven decisions at TD, a leading North American financial institution.

Posted 9/10/2026full-timeToronto • 🇨🇦 CanadaMid-LevelSenior💰 CA$120,000 - CA$154,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced analytics and AI/ML methodologies, with a strong ability to translate complex data into actionable insights for financial services and retail banking. Proficient in developing scalable analytics assets and collaborating with cross-functional teams to drive data-driven decision-making.

Highest-signal resume keywords

Advanced AnalyticsMachine LearningData VisualizationPython ProgrammingCloud Services (Azure/AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningPredictive AnalyticsData PipelinesSQLPySparkPower BIDatabricksNLPModel Development

Soft Skills

StorytellingRelationship ManagementBusiness Communication

Tools & Technologies

Azure Machine LearningKubernetesDockerTableauApache SparkSnowflake

Industry Keywords

Financial ServicesRetail BankingC-suite StakeholdersData ScienceAI/ML Adoption

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDockerETLKubernetesPySparkPythonPyTorchSparkSQLTableau

About the role

Key responsibilities & impact

Lead end-to-end performance diagnostics across customer, product, and advisor dimensions
Translate curated data into actionable insights through hypothesis development, testing, analysis, and stakeholder storytelling
Design and deliver scalable analytics assets, including datasets, dashboards, segmentation frameworks, and predictive AI/ML models
Investigate, evaluate, and implement AI/ML tools and algorithms for complex business problems
Develop visualizations and data stories for technical and non-technical audiences
Partner with business owners to drive advanced analytics and AI/ML adoption
Lead collaboration with data scientists, engineers, IT partners, and business process owners
Provide subject-matter expertise, mentorship, and guidance on advanced analytics and AI/ML methodologies
Identify emerging analytical trends and data needs to improve repeatable and scalable solutions

Requirements

What you’ll need

Strong ability to frame and structure complex business problems in financial services / retail banking
Demonstrated ability to connect analytical insights to commercial levers and influence senior executives and C-suite stakeholders
Experience creatively exploring data, identifying non-obvious patterns, and rigorously testing hypotheses
Experience working with existing ML/AI models and building or modifying models
Solid knowledge of applied Machine Learning, Deep Learning, and Large Language Models
Solid cloud experience with Azure or AWS and services including Databricks, Kubernetes, Docker, Azure Machine Learning, and Azure Data Factory
Proficiency in Python, PySpark, SQL, Power BI, and Databricks or similar platforms
Strong experience with PySpark for big data processing and PyTorch for deep learning model serving
Experience with structured and unstructured data, data pipelines, and analytical assets
Strong relationship management, storytelling, and business communication skills
A graduate or undergraduate degree in a quantitative or analytics-focused discipline
5 years of relevant experience in advanced analytics, data science, or applied AI/ML
Knowledge of predictive analytics, NLP, supervised and unsupervised learning, Generative AI tools and APIs, model development and deployment, experimentation and optimization
Experience with Power BI, Tableau, Azure, Snowflake, ETL/ELT pipelines, and Apache Spark
Bilingual proficiency in English/French is nice-to-have
For Quebec roles, mastery of a language other than French to support employees or colleagues requiring services in another language

Benefits

Comp & perks

Base salary and variable compensation
Health and well-being benefits
Savings and retirement programs
Paid time off
Banking benefits and discounts
Career development
Reward and recognition programs
Regular development conversations, training programs, and a competitive benefits plan
Online learning platform
Mentoring programs
Training and onboarding sessions
Accessibility accommodations, including accessible meeting rooms and captioning for virtual interviews