Senior Data Scientist and Team Lead

at  National Bank of Canada

A career as a Senior Data Scientist and Team Lead in the Risk Modeling and Strategies team means developing risk decision models for personal financing products. It also involves guiding and coaching your team members on decision-making strategies to achieve common objectives.

REQUIREMENTS:

• Bachelor’s or Master’s degree in a quantitative field, 3-5 years of experience in modeling, decision strategies, or other relevant data science roles
• Experience in a coaching and influencing role
• Proficiency in statistical/econometric models and machine learning
• Expertise in statistical programming tools like SAS/SQL (R or Python)
• Knowledge of personal credit products and risk management.
  Your benefits

In addition to competitive compensation, upon hiring you’ll be eligible for a wide range of flexible benefits to help promote your wellbeing and that of your family.

• 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
• Opportunities to get involved in community initiatives
• Telemedicine service
• Virtual sleep clinic

These are a few of the benefits available to you. 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 actively listen to employees’ ideas. Whether through our surveys or programs, regular feedback and ongoing communication is encouraged.

• Support and coach two senior data scientists in model development and ensure smooth progression of activities
• Communicate model results and the progress of initiatives in various committees
• Organize and lead discussions with business line and risk management partners for model approval
• Act as a subject matter expert on certain strategic initiatives
• Oversee, alongside the team and partners, the deployment of models in decision engines
• Ensure post-production follow-up of developed models
• Advance expertise and maturity of strategies by exploring new data sources (internal or external) or new modeling techniques like artificial intelligence
• Collaborate with other team leads to define the vision for the department and plan business strategies.