Senior Data Analyst

About the role

At EQ, we are remaking banking so every Canadian gets ahead, every day, serving nearly 4 million Canadians from coast to coast with a wide variety of financial services from banking and lending to trust and credit union solutions. We have been at this since 1970, challenging the conventions of traditional banking with smarter, faster, and more connected financial experiences that define our challenger identity. What has kept us moving are the people behind it all, the challengers who ask better questions, push back on old assumptions, and look for a better way forward every single day. If you are driven to help reshape how banking works for Canadians and the businesses that power our economy, this role offers a direct path to contribute to that mission in a meaningful and impactful way. As a Senior Data Analyst on the Activation, Next Best Action team, you will own the end to end analytics lifecycle for critical growth initiatives, from problem framing and data discovery through insight generation and executive facing storytelling. You will act as the primary data strategist for Next Best Action programs, partnering closely with product, marketing, and risk teams to design measurement frameworks and evaluate the true impact of customer journeys. You will translate ambiguous business problems into analytical roadmaps, defining the metrics, segments, and experiments that prove what moves the needle on activation, engagement, and long term customer growth. This is a pivotal role for someone who wants to turn complex data into clear, actionable strategies that directly influence how we acquire, activate, and retain customers across our portfolio.

Key facts

What you'll do

Analyze end to end customer journeys across onboarding, activation, and engagement to identify friction points and opportunities for optimization using advanced analytics and modeling techniques.

Develop and maintain a repeatable methodology to evaluate Next Best Action strategies, defining test structures, success metrics, and learning loops that scale across channels and products.

Partner with cross functional stakeholders to translate business objectives into analytical requirements, ensuring data needs are aligned with product roadmaps and customer lifecycle strategies.

Design and implement tracking frameworks and data quality checks that capture the full scope of customer interactions, enabling robust measurement of channel performance and profitability.

Build and iterate on customer segmentation and propensity models that power personalization at scale, improving relevance and long term value for different customer cohorts.

Lead the analysis of credit card portfolio performance, integrating behavioral, transactional, and risk data to support effective credit risk management and product decisioning.

Create clear, executive facing narratives backed by data, using visualization and storytelling techniques to make complex insights accessible to leaders across banking, risk, and marketing functions.

Champion a culture of experimentation by designing measurement plans for campaigns and interventions, monitoring lift, and feeding learnings back into future strategies.

Identify and operationalize advanced analytical techniques where appropriate, ensuring the team leverages best in class methods to solve high impact business problems.

Act as the analytical backbone for the Activation, Next Best Action team, providing documentation, data dictionaries, and reusable logic that other analysts and business partners can rely on.

Collaborate with data engineering partners to ensure data pipelines, warehouses, and models support timely, accurate, and reproducible analysis.

Support the governance of analytics assets, ensuring standards are met, insights are traceable, and the organization can audit and trust the results it uses.

Continuously scan the competitive and regulatory landscape for emerging practices in data driven banking, bringing back insights that can inform EQ's next wave of innovation.

Own the end state reporting for key initiatives, ensuring stakeholders have the clarity and confidence to make fast, data backed decisions.

Requirements

You hold a Bachelor's degree in a quantitative field such as statistics, mathematics, computer science, or a related discipline that provides a strong foundation in analytical thinking.

You bring 5+ years of progressive experience in data analysis, business intelligence, or a related role, with a proven track record of turning data into business impact.

You have hands on experience with SQL and at least one modern analytics tool or programming language such as Python or R, enabling you to manipulate data and build models independently.

You are fluent in statistical concepts and comfortable using data to test hypotheses, measure outcomes, and interpret results with a rigorous, methodical mindset.

You have a demonstrated history of creating dashboards, reports, and visualizations that help non technical stakeholders understand complex information and take action.

You understand customer lifecycle management and have experience analyzing behavior across digital and physical channels in a financial services context.

You are comfortable working in a fast paced, ambiguous environment where priorities can shift quickly and you must deliver clear answers under tight timelines.

You communicate in a clear, structured manner, able to translate technical findings into recommendations that resonate with both technical and executive audiences.

Nice to have

Experience in financial services, banking, or credit risk analytics, with a focus on credit card portfolios and related risk metrics.

Background in managing analytics in regulated environments, where compliance, auditability, and data governance are critical.

Familiarity with machine learning techniques for classification or uplift modeling, applied to customer activation and retention problems.

Knowledge of marketing attribution methods and experimentation frameworks used to measure channel and campaign effectiveness.

Experience with data visualization platforms such as Tableau, Power BI, or Looker, and with dashboard design best practices.

Practical notes

The role is based in Toronto, requiring attendance a few times per month for in person collaboration.

No sponsorship is available for this position at this time.