Data Scientist

Role overview

Scotiabank is looking for an advanced Data Scientist to join its Customer Insights Data and Analytics group in Toronto, Ontario. This position focuses on producing analytics and practical insights that strengthen understanding of customer experience and the full client journey across the bank’s business lines. The work is intended to surface opportunities that improve outcomes for customers and the business alike. The successful candidate will combine strong communication and data storytelling with deep analytical ability, using AI/ML, experimentation, visualization, and Python to tackle high-impact business problems tied to customer experience and journey performance.

What you will do

As part of the CID&A team, you will collaborate with business lines and stakeholders to identify where analytics can enhance customer experience and optimize the client journey. You will work alongside data scientists, data engineers, product partners, and business stakeholders to define problems, examine data across multiple touchpoints, and convert insights into scalable recommendations and solutions. Your work will help reveal the factors behind customer behavior, pain points, and critical moments in the journey, while also taking the bank’s risk appetite and risk culture into account when decisions are made.

Technical delivery and development

• Build, validate, and deploy analytical methods that reveal meaningful patterns in client behavior, experience, and journey performance across channels and touchpoints.
• Develop and maintain strong Python and SQL code to extract, prepare, and analyze large structured and unstructured datasets, including reliable analytical pipelines.
• Apply statistical, machine learning, and exploratory techniques to uncover what drives customer satisfaction, friction in the journey, and opportunities to improve engagement, retention, and overall experience.
• Produce dashboards, reports, and visualizations that clearly present insights, trends, and business opportunities to operational, executive, and other stakeholders.
• Keep current with advances in AI, machine learning, experimentation, visualization, and data science practices, and contribute to research and development that uses design thinking and advanced analytics to improve the client journey.

Collaboration and strategy

• Support high-impact analytics initiatives across multiple business lines by delivering insights that reduce journey friction and create value for customers and the organization.
• Work with stakeholders to turn business questions and customer experience challenges into scalable analytical solutions using available data assets and reusable components.
• Consider the bank’s risk appetite and risk culture when contributing to model development and deployment decisions.
• Partner effectively with data scientists, data engineers, software engineers, product owners, and business teams to build scalable analytics, insight frameworks, and measurement approaches across the bank.

Skills and qualifications

The ideal candidate will have expert-level Python skills for data manipulation, statistical modeling, and pipeline development, along with hands-on experience applying AI and machine learning to business problems. Experience in customer experience, customer behavior, journey analytics, or insights generation is especially relevant. You should be comfortable framing ambiguous problems with stakeholders, defining hypotheses, selecting meaningful metrics, and translating analysis into practical recommendations. Strong analytical capability in areas such as statistical analysis, segmentation, predictive modeling, prompt engineering, and similar methods is important. You should also have experience with big data tools such as SQL, Hadoop, and Spark; cloud analytics environments like Google Cloud and Microsoft Azure; and working with large volumes of structured and unstructured data from multiple sources. Familiarity with DevOps and software engineering practices such as Git, continuous integration/delivery, and Jira is also valued. The role requires a university or postgraduate degree in a relevant STEM discipline, along with strong communication skills, the ability to produce clear documentation and presentations, and the talent to turn technical findings into business value. Expert-level use of visualization tools such as Power BI is also expected.

About Scotiabank

Scotiabank is a major banking organization operating across the Americas and guided by its purpose, “for every future.” The bank supports customers, families, and communities through a broad range of services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets. The organization emphasizes inclusion, accessibility, and the varied experiences each person brings to the workplace.

What the company offers

• An opportunity to join a forward-looking team working at the forefront of AI use in financial services.
• Access to a rewarding career path with varied professional development opportunities and internal support to grow your skills.
• A competitive compensation and benefits package.
• An inclusive, collaborative environment that values creativity, curiosity, and shared success.
• A company culture that is committed to making a positive difference in communities for both employees and customers.

Accessibility and hiring notes

Scotiabank is committed to maintaining an inclusive and accessible hiring process. Candidates who need accommodations during recruitment or selection may request support such as an accessible interview location, alternate-format documents, an ASL interpreter, or assistive technology. Applicants must submit their application directly online to be considered. Only candidates selected for an interview will be contacted.

Location

This position is based in Toronto, Ontario, Canada.