Full Stack Data Science Engineer

• 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

• 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

Core Competencies

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 Analytics
• Machine Learning
• Data Visualization
• Python Programming
• Cloud Services (Azure/AWS)

Hard Skills

• Machine Learning
• Deep Learning
• Predictive Analytics