About this role
Job title: Data Scientist
About the Role Scotiabank is seeking a highly specialized Data Scientist to join the Customer Insights Data and Analytics team. This role centers on delivering analytics and actionable insights to deepen understanding of client experience and the end-to-end client journey across the bank’s business lines, helping identify opportunities to improve outcomes for both clients and the business.
What You'll Do
- Develop, test, and implement analytical approaches that uncover meaningful patterns in client behaviour, experience, and journey performance across multiple channels and touchpoints.
- Write and maintain high-quality Python and SQL code to source, prepare, and analyze large volumes of structured and unstructured data, building robust analytical datasets and pipelines.
- Design and apply statistical, machine learning, and exploratory analytical techniques to identify drivers of client satisfaction, friction points in the client journey, and opportunities to improve engagement, retention, and overall experience.
- Create compelling data visualizations, dashboards, and reports that clearly communicate insights, trends, and opportunities related to client experience and client journey performance to business and executive stakeholders.
- Stay up to date on advances in AI, machine learning, experimentation, visualization, and data science best practices. Support research and development focused on applying design thinking and advanced analytical techniques to better understand and improve the client journey.
What We're Looking For
- Strong storytelling and communication skills, with the ability to translate complex data into clear, actionable insights.
- Deep analytical expertise in data science, analytics, and problem solving across client experience and journey performance.
- Proficiency with AI/ML, experimentation, visualization, and robust Python skills to solve high-impact business challenges.
- Experience collaborating with diverse teams of data scientists, data engineers, product partners, and business stakeholders to frame problems and drive scalable recommendations.