Senior Data Scientist

Description

A career as a senior data scientist within the Financial Crime team at National Bank means contributing to the evolution of analytical capabilities and fraud risk management strategies through advanced expertise in data science. This role gives you the opportunity to make a tangible impact on the prevention and detection of banking fraud by developing models, analytical approaches and innovative solutions that support decision-making and reduce financial losses.

Your role

• Develop, maintain and optimize statistical and machine learning models aimed at improving fraud prevention and detection.
• Conduct complex analyses and interpret data to identify emerging trends and risks, and support decision-making in fraud risk management.
• Develop and optimize fraud prevention and detection strategies, and recommend analytical approaches to improve their effectiveness.
• Collaborate with operational teams and various partners to deliver high-impact analytics and modelling initiatives and address their business needs.
• Contribute to the sector’s strategic direction by anticipating evolving fraud risks and proposing new approaches to mitigate them.
• Ensure compliance with standards related to model development, monitoring and documentation, and contribute to projects or initiatives requiring advanced data science expertise.
  

Your team

Within the Financial Crime sector, you’ll be part of a team of four colleagues and report to the Senior Manager, Analytics – Fraud Risk Management. Our team stands out for its strong analytical capabilities and key role in preventing risks to the Bank. We aim to offer you maximum flexibility to support your quality of life, including a hybrid work model and flexible schedules.

The Bank values continuous development and internal mobility. Our personalized training programs, based on learning through experience, help you master your role and develop new areas of expertise. 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.

Prerequisites

• Bachelor’s degree or master degree and 4 to 6 years of relevant experience 
• Experience in financial crime prevention or fraud risk management.
• Proficiency in data modelling and visualization techniques (SAS, SQL, Python and Power BI).
• Strong analytical and problem-solving skills.