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Data Science Bank Jobs in Toronto, ON (NOW HIRING)

Data Scientist II

Toronto, ON ยท On-site

CA$81K - CA$115K/yr

It supports most consumer facing TD Bank Group lines of business. The Digital Marketing Analytics ... science and modelling, business intelligence, data strategy and governance, data management and ...

Data Scientist II

Markham, ON ยท On-site

CA$81K - CA$115K/yr

In-depth knowledge of data science tools such as NumPy, pandas, matplotlib or R equivalent ... Together, we are reimagining what banking can be for our clients, colleagues and communities. Our ...

As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and ... Your work will sit at the intersection of advanced data science and real-world financial systems ...

As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and ... Your work will sit at the intersection of advanced data science and real-world financial systems ...

We're building a relationship-oriented bank for the modern world. We need talented, passionate ... Data Science Expertise: Provide advanced analytics solutions to solve business problem leveraging ...

We're building a relationship-oriented bank for the modern world. We need talented, passionate ... Data Science Expertise: Provide advanced analytics solutions to solve business problem leveraging ...

... Banking. What You Will Bring to Succeed Education: * Bachelor's degree in Computer Science, Data Science, Information Technology, Business Administration, or a related field. * Master's degree (e.g ...

Data Scientist II

Toronto, ON ยท On-site

CA$81K - CA$115K/yr

The Canadian Personal Banking (CPB) AI2 team supports the day-to-day activities of the CPB ... science) Graduate's degree preferred, with progressive project work experience * 3+ year of ...

Showing results 21-40

Data Science Bank information

See Toronto, ON salary details

$20.5K

$103.2K

$193.7K

How much do data science bank jobs pay per year?

As of Sep 2, 2026, the average yearly pay for data science bank in Toronto, ON is $103,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,194.00 and $147,445.00 per year, depending on experience, location, and employer.

What does a data scientist do in a bank?

A Data Science professional in a bank leverages data analysis, statistical modeling, and machine learning to solve business problems and improve decision-making. Their work often involves analyzing customer behavior, detecting fraud, assessing credit risk, and optimizing marketing strategies. They collaborate with other departments to turn raw data into actionable insights, ensuring the bank remains competitive and compliant with regulations. By building predictive models and dashboards, they help the bank enhance efficiency, profitability, and customer satisfaction.

What are the key skills and qualifications needed to thrive as a data scientist in banking?

To thrive as a Data Scientist in banking, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with machine learning libraries, and knowledge of data visualization and big data platforms such as SQL, Hadoop, or Spark are crucial. Exceptional problem-solving abilities, attention to detail, and effective communication skills help you translate complex data insights into actionable strategies for non-technical stakeholders. These skills ensure accurate risk assessment, fraud detection, and data-driven decision-making in the highly regulated financial sector.

How does a data scientist at a bank typically contribute to cross-functional teams, and what collaboration challenges might they face?

As a Data Scientist in a banking environment, you will frequently collaborate with teams from IT, risk management, marketing, and business strategy to develop data-driven solutions. This might involve translating complex analytical findings into actionable insights for non-technical stakeholders or integrating models into existing business processes. Common challenges include aligning data science objectives with business goals, managing data privacy concerns, and ensuring clear communication across different departments. Building strong relationships and maintaining open communication channels are essential for overcoming these challenges and delivering impactful results.

What job categories do people searching Data Science Bank jobs in Toronto, ON look for?

The top searched job categories for Data Science Bank jobs in Toronto, ON are:

Infographic showing various Data Science Bank job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $103,158 per year, or $49.6 per hour.

Senior Data Scientist Model Developement and Validation

National Bank

Richmond Hill, ON โ€ข Hybrid

Full-time

Medical, Retirement

This job post hasย expired today.ย Applications are no longer accepted.


Job description

As a Senior Data Scientist in the Credit Risk Analytics team at National Bank, youโ€™ll be responsible for the IFRS 9 and stress testing model development and performance monitoring, as well as IFRS 9 reporting and analytics. This role will also need to support other closely related risk functions that includes RWA, Economic Capital and stress testing. With your experience in credit risk modeling , strong analytical skills , and knowledge of IFRS 9 and regulatory requirements , youโ€™ll have a positive impact on NBCโ€™s credit risk management through building advanced models, efficient and robust risk processes and providing insightful analyses to our senior management . Your role: Develop and recalibrate IFRS 9 and stress testing models for the Bankโ€™s wholesale and retail portfolios. Document the data selection, modeling techniques and implementation. Conduct model backtesting, monitor model performance and propose appropriate model actions when necessary. Keep abreast of up-to-date modeling methodologies, tools and regulatory requirements. Conduct IFRS 9 ECL impact assessment for parameter recalibration, economic scenario change, model updates, data migration and process changes. Work with IFRS 9 production team to implement and test IFRS 9 model changes. Validate the process inputs and outputs for quality control and governance. Collaborate with Model Validation, Model Governance, Audit by preparing supporting materials, addressing questions and concerns, and ensuring IFRS 9 model changes are appropriately documented and understood. Provide in-depth analysis on IFRS 9 results and identify key drivers for ECL movements. Provide support for ad-hoc requests required by IFRS 9 stakeholders and senior management in a precise and efficient manner. Contribute to strategic risk initiatives by using analytical skills to project potential losses and make recommendations to limit risk. Demonstrate insight into internal client's business and develop innovative solutions that create value. Your team: As part of the Credit Risk Analytics sector, youโ€™ll be on a team of 24 of colleagues and youโ€™ll report to the Senior Director - Analytics. Our team stands out for expertise in model development, model implementation and risk reporting in IFRS 9, stress testing and capital areas. As some processes are part of the Bankโ€™s month-end or quarter-end reporting to the public or to the regulators, we may work under tight deadline and pressure sometimes. We offer a wide range of ongoing learning opportunities for your development, including coaching, hands-on learning, training courses and through the collaborating with colleagues who have varied expertise and profiles such as in-depth data analytics, model development, risk programming and presentation to senior management. Prerequisites: Masters or PhDs in a relevant field such as Financial Engineering, Finance, Economics, Statistics, Mathematics, Computer Science and Data Science. Minimum 2-3 years of professional experience in quantitative model development or validation for retail or wholesale credit risk. Hands-on experience in managing, reconciling, and interpreting large and complex enterprise level data sets. Knowledge with IFRS 9 and regulatory requirements. Hands-on experience with SAS, Python, MS Excel (VBA) or SQL. Excellent analytical skills to identify the causes of risk changes and impact to business and strategy. Ability to effectively communicate the analysis and explain the results in a simple and concise way. Strong attention to details and the ability to understand the big picture. Demonstrated ability to work under pressure and tight deadline. Exceptional critical thinking skills, learning skills and ability to work independently with limited guidance. Completion or progression in CFA and/or FRM would be an asset. Completion of SAS certification would be an asset. Completion of SAS certification would be an asset. Your benefits In addition to competitive compensation, upon hiring youโ€™ll be eligible for a wide range of flexible benefits to help promote your wellbeing and that of your family such as: * Health and wellness program, including many options * Flexible group insurance * Generous pension plan * Employee Share Ownership Plan * Employee and family assistance program * Preferential banking services * Involvement in community initiatives * Telemedicine service * Virtual sleep clinic We have an offer that keeps up with trends as well as your needs and those of your family. Our dynamic work environments and cutting-edge collaboration tools foster a positive employee experience. We value employeesโ€™ ideas. Whether through our surveys or programs, regular feedback and ongoing communication are encouraged. Making a bold move in a people-first environment Weโ€™re a bank on a human scale that stands out for its courage, entrepreneurial culture, and passion for people. Our mission is to have a positive impact on peopleโ€™s lives. Our core values of partnership, agility, and empowerment inspire us, and inclusion is central to our commitments. We aim, wherever possible, to provide a barrier-free and accessible environment to all employees. We strive to provide accessibility measures throughout the recruitment process within the limits of our available resources. If you require accommodations, feel free to let us know during our initial conversations. We welcome all candidates! What can you bring to our team? Join us! Artificial Intelligence, Communication, Python, Teamwork, Business Acumen, Data-Driven Decision-Making, Detail-oriented, Initiative, Learning Agility, Resiliency, Prioritization, Analytical thinking, Data pipeline, Exploratory Data Analysis, Self-Sufficiency