Senior Quantitative Manager to develop predictive models and analysis for a large banking client 48424
Job Type: Contract
Positions to fill: 1
Start Date: Feb 06, 2023
Job End Date: Apr 08, 2025
Pay Rate: Hourly: Negotiable
Job ID: 126951
Location: Toronto
Job ID: 48424
# of positions: 1
Duration: 18 months
Extension possible: possible
Conversion Possible: possibility
Interview Process: 1 round – WebEx
Work Location (Remote, Hybrid or Both?): hybrid – once a week in office (only in office Tuesdays)
Summary
The Treasury and Financial Modelling group is part of the Corporate Data & Analytics (D&A) group within Corporate Transformation & Operations (CTO) at TD Bank. It is responsible for providing expertise in specialized analytical techniques as a shared service to the Corporate Segments of the bank.
The position reports to Senior Manager, Customer Behaviour Modelling team within the Treasury and Financial Modelling group. Detailed accountabilities include
• Develop predictive models and analyses to perform pre-provision net revenue (PPNR) projection for use in the Bank's stress testing programs
• Develop, present, document, and back-test various statistical and econometric customer behaviour models and analytics to support treasury and forecasting priorities across the corporate functions
• Conduct sensitivity analyses to assess the impact of model assumptions on the bank’s margins and risk metrics.
• Assist with building automated tools and data extraction frameworks.
• Research industry best practice, address model validation, audit and regulatory requirements and/or findings in a timely manner
• The position must work effectively with business partners, including Treasury and Balance Sheet Management (TBSM), the Treasury Analytics Group, Finance, and the Model Validation and Management Team, to ensure the soundness and accuracy of the model development and implementation.
Must Have:
# of positions: 1
Duration: 18 months
Extension possible: possible
Conversion Possible: possibility
Interview Process: 1 round – WebEx
Work Location (Remote, Hybrid or Both?): hybrid – once a week in office (only in office Tuesdays)
Summary
The Treasury and Financial Modelling group is part of the Corporate Data & Analytics (D&A) group within Corporate Transformation & Operations (CTO) at TD Bank. It is responsible for providing expertise in specialized analytical techniques as a shared service to the Corporate Segments of the bank.
The position reports to Senior Manager, Customer Behaviour Modelling team within the Treasury and Financial Modelling group. Detailed accountabilities include
• Develop predictive models and analyses to perform pre-provision net revenue (PPNR) projection for use in the Bank's stress testing programs
• Develop, present, document, and back-test various statistical and econometric customer behaviour models and analytics to support treasury and forecasting priorities across the corporate functions
• Conduct sensitivity analyses to assess the impact of model assumptions on the bank’s margins and risk metrics.
• Assist with building automated tools and data extraction frameworks.
• Research industry best practice, address model validation, audit and regulatory requirements and/or findings in a timely manner
• The position must work effectively with business partners, including Treasury and Balance Sheet Management (TBSM), the Treasury Analytics Group, Finance, and the Model Validation and Management Team, to ensure the soundness and accuracy of the model development and implementation.
Must Have:
- 5+ years of working experience in advanced data analytics / predictive modelling, preferably in the financial industry.
- Graduate degree in Statistics/Mathematics/Economics/Computer Science/Actuarial Science/Finance/Engineering or equivalent (e.g., CFA or FRM).
- Experience with pre-provision net revenue (PPNR) modelling will be an asset.
- Working knowledge of financial markets as well as fixed income portfolio management techniques and valuation models.
- Solid "hands-on" experience with building databases using SQL programming, Python, Excel VBA and C++ programming.
- Experience with statistical methods and libraries (e.g. SPSS, SAS, R)
