Description
A career as a Senior Data Analyst in the Real Estate Portfolio Management team at National Bank involves acting as a liaison between the business team and the data analysis teams.
Your Job:
- Understand the business needs in real estate and commercial financing and structure data analysis and modeling action plans to provide information to the sales force on pricing, profitability, and client advice.
- Support the development of analytical models and visualization solutions to maximize the use of our databases to improve pricing, profitability, and commercial real estate client advice.
- Participate in multiple business intelligence projects by supervising front-end and back-end development, ensuring quality control, and coordinating production with multiple stakeholders.
- Ensure the reliability, performance, and evolution of analytical models and visualization solutions.
- Create and review documentation for models and solutions, support their production, and ensure the integration and technical supervision of projects.
- Support and train users on the use and content of models and solutions to maximize the adoption of developed solutions.
- All these activities are carried out while respecting and promoting the artificial intelligence and data strategy standards established by the organization.
Your Team:
Under the direction of the Senior Director of the Real Estate Portfolio Management team, you act as a professional reference in business intelligence project management by offering expertise and advice in modeling, visualization, and data science.
National Bank values continuous development and internal mobility. Our personalized training programs, based on learning in action, allow you to master your profession and develop new areas of expertise. Tools such as the Data Academy, language training, the Harvard Learning Center, and coaching and mentoring support are available to you at all times.
Prerequisites:
- University degree and several years of experience in business intelligence, operations research, applied statistics, data mining, and machine learning.
- Ability to participate and present in multidisciplinary and multi-level stakeholder meetings, skills to synthesize and communicate in non-technical language.
- Mastery of complex and multi-dimensional database analysis.
- Advanced knowledge in statistical and predictive modeling, machine learning, and clustering, recommendation, and optimization algorithms.
- Advanced knowledge in data analysis tools such as SAS, SQL, and visualization tools such as Power BI and Tableau.
- Knowledge of the banking sector.
