Senior Manager, Analytics & Insights

Scotiabank•Toronto, ON

1d•Onsite

About The Position

The Senior Manager, Analytics & Insights leads a high-performing analytics team to deliver actionable insights and enterprise-grade reporting solutions. This role bridges complex data engineering with strategic business decision-making. You will own a broad portfolio of analytics products, mentor managers, and senior practitioners, and help shape the organization’s data culture as we transition to modern cloud-based architectures.

Requirements

Bachelor’s or master’s degree in a quantitative discipline (e.g., Business Analytics, Computer Science, Statistics, Finance, or Engineering)
8+ years’ experience in Analytics, Business Intelligence, or Data Science
People leadership experience is required
Expert-level proficiency in Power BI (DAX, Power Query) or comparable BI platforms
Advanced SQL / Python skills for complex data extraction, transformation, and optimization.
Experience working in cloud environments (Azure ecosystem, Snowflake, or GCP) with strong data modeling foundations
Exceptional communication, stakeholder management, and team leadership skills

Nice To Haves

Prior experience in Banking, Wealth Management, or Financial Services is highly desirable—particularly within distribution, compliance, or regulatory environments
Knowledge of Canadian Retail Banking and Wealth Management distribution channels

Responsibilities

Provide strategic direction and day-to-day leadership to a team of Analytics Managers, and Senior Analysts
Act as a mentor to Analytics Managers, strengthening capabilities in people leadership, delivery management, and technical storytelling
Build a culture of accountability, continuous improvement, and technical excellence through clear expectations and ongoing feedback
Serve as a trusted analytics partner to senior leaders across Compliance & Supervision, SGAM Finance and Retail Mutual Funds Distribution
Own and govern a diverse ecosystem of dashboards and reporting assets, ensuring accuracy, performance, scalability, and alignment to business KPIs
Balance competing priorities across business units with transparent communication on delivery timelines, trade-offs, and capacity constraints
Partner closely with Engineering to design reusable, well-modeled datasets that reduce manual effort and downstream reporting complexity
Lead the shift from legacy, ad hoc reporting toward automated, self-service analytics solutions
Support the evolution of the analytics stack (e.g., Hadoop to Azure / Microsoft Fabric), ensuring reporting stability and continuity throughout migration efforts
Champion the move from descriptive analytics to predictive and prescriptive insights
Define and enforce standards for data visualization, query optimization, documentation, and code quality (DAX / SQL / Python)
Partner with GWM Data Governance to ensure all analytics and reporting meet regulatory, privacy, and audit requirements