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 Robust 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 #J-18808-Ljbffr

📌 Full Stack Data Science Engineer (Toronto)
🏢 Jobtailor
📍 Toronto