Senior Data Scientist

A career as a Senior Data scientist or Senior Data scientist in the modelling and risk strategies team at National Bank means acting as a specialist in credit risk management decision-making strategies. This position allows you to have a positive impact on our organisation thanks to your expertise in statistical modelling, machine learning and behavioural data analysis.

Your job

• Develop statistical models and decision-making strategies for loans to individuals and small and medium-sized businesses in order to optimise credit risk and profitability.
• Analyze behavioural data and translate the results into concrete recommendations that support business line growth objectives.
• Assess the performance of models and strategies in place, particularly based on a Champion-Challenger approach, then recommend the adjustments required.
• Document strategies and prepare the elements needed for their review and approval.
• Coordinate the implementation of strategies with it partners and carry out acceptance tests.
• Communicate the progress of work in agile mode and collaborate with risk management teams and business lines.

Your team  

In the risk modelling and strategies sector, you are part of a team of 12 advanced analytics specialists and report to the Senior Manager – risk models and strategies. The team is responsible for modelling activities and risk strategies for credit cards, personal financing and small and medium-sized businesses, from credit origination to life cycle management. It stands out for its collaboration, analytical rigour and proximity to business partners.

Our goal is to offer you maximum flexibility to promote your quality of life. This includes a hybrid work environment and a flexible, adaptable schedule.

The Bank values continuous development and internal mobility. Our personalised training programs, based on on on-the-job learning, help you master your profession and develop new fields of expertise. Tools such as the Data Academy, Language Training, the Harvard Learning Centre and coaching and mentoring support are available to you at any time.

Prerequisites

• A bachelor's or master's degree in a quantitative field and two to three years of experience in modelling, decision-making strategies, data science or a related function.
• Experience in developing statistical, econometric or machine learning models
• Be familiar with personal and commercial credit products and credit risk management principles.
• Proficiency in Python, R, SQL or SAS for statistical analysis and modelling.
• Know how to assess the performance of models and decision-making strategies based on business data.