Senior Data Scientist

A career as a Senior Data Scientist within the Credit Risk and Climate Stress Testing team at National Bank means contributing to the development of quantitative models and conducting stress tests to assess the impact of various economic and climate scenarios on the Bank. This role allows you to make a positive impact on our organization by leveraging your expertise in modelling, programming, and complex data analysis.

Your role

• Participate in stress-testing exercises and regulatory analyses aimed at assessing the impact of various economic scenarios on the Bank’s credit portfolio.
• Develop and enhance quantitative models and stress-testing methodologies to improve their efficiency and accuracy.
• Optimize and automate existing processes to reduce manual intervention and accelerate the delivery of analyses.
• Collaborate with Economists, Finance, and Capital teams to analyze results and contribute to the Bank’s financial projections.
• Analyze, simplify, and present stress-testing results, with opportunities to progressively contribute to presentations for senior management and regulatory authorities.
• Contribute to the development of climate scenario analyses, particularly with respect to physical and transition risks.

Your team

Within the Credit Analytics and Integrated Risk Management sector, which brings together 140 colleagues, you will be part of a five-person team and report to the Senior Manager, Stress Testing. Our team stands out for the diversity of its expertise in economics, applied mathematics, and quantitative modelling.

You will work in an environment where you can contribute to improving models and optimizing processes, while benefiting from the expertise of experienced colleagues to further develop your skills.

You will enjoy a hybrid work environment, with an expectation of being in the office 40% of the time, particularly on team collaboration days.

The Bank values continuous development and internal mobility. Our personalized training programs, based on learning through hands-on experience, allow you to strengthen your expertise and develop new areas of specialization. Resources such as the Data Academy, language training, Harvard Learning Center, as well as coaching and mentoring support, are available to you at all times.

Requirements

• Bachelor’s degree and five years of relevant experience, or a master’s degree and three years of relevant experience in mathematics, statistics, economics, finance, financial engineering, econometrics, or a related field.
• Strong knowledge of quantitative modelling, acquired through academic studies or professional experience.
• Demonstrated programming skills, particularly with SAS, SQL, Python, or other programming and automation languages.
• Strong analytical skills, attention to detail, and autonomy, combined with initiative and the ability to manage priorities under tight deadlines.
• Excellent communication skills and the ability to explain complex technical concepts clearly, as well as the ability to collaborate effectively with various stakeholders.
• Knowledge of credit risk modelling, stress testing, IFRS 9 standards, or risk-weighted assets (RWA) is considered an asset.