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TD

Senior Modelling / Forecasting Analyst, Quants

TD

. Conduct independent validation of Treasury, Liquidity Risk Management, IRRBB aggregation, and Customer Behavior forecast models .

Posted 9/17/2026full-timeToronto • CanadaSenior💰 CA$81,600 - CA$115,200 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates advanced quantitative skills and technical proficiency in Python, SQL, SAS, and VBA for model validation and development in liquidity risk management. Capable of conducting comprehensive validation testing and communicating findings effectively to stakeholders.

Highest-signal resume keywords
Model ValidationStatistical ForecastingPython ProficiencyFinancial Risk ManagementTechnical Writing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Quantitative AnalysisModel DevelopmentStatistical AlgorithmsTime-Series ModelsData Quality AssessmentValidation TestingFinancial Products KnowledgeAI Agent WorkflowsData Pipeline ProcessesRisk Management
Soft Skills
Analytical SkillsProblem-Solving SkillsAttention to DetailTime ManagementCommunication Skills
Tools & Technologies
PythonSQLSASVBAJSONScala
Certifications & Qualifications
CFAFRM
Industry Keywords
Liquidity Risk ManagementModel GovernanceDFASTEWSTMSTBusiness Requirement DocumentsAudit ReviewsBanking Treasury ReportingData ControlOperational Risk Management

Tech Stack

Tools & technologies
PythonScalaSQLVBA

About the role

Key responsibilities & impact
  • Conduct independent validation of Treasury, Liquidity Risk Management, IRRBB aggregation, and Customer Behavior forecast models
  • Validate models for ALM, FTP pricing, IRRBB, and stress testing, including DFAST, EWST, and MST
  • Develop and execute comprehensive validation testing plans according to enterprise model validation procedures
  • Review measurement choices, liquidity and business assumptions, and Business Requirement Documents for consistency with approved approaches
  • Assess statistical and mathematical algorithms, modelling approaches, assumptions, and alignment with industry best practices
  • Assess data quality, input controls, and governance processes
  • Conduct validation testing from data enrichment through final model outputs and performance
  • Assess model governance and control adequacy
  • Develop issue logs, identify limitations, and communicate issue severity to stakeholders for resolution
  • Draft model validation reports supporting validation conclusions and audit or regulatory reviews
  • Maintain and develop quantitative analysis knowledge in liquidity risk management
  • Support standards and procedures for model vetting and validation
  • Support senior management responses to Canadian and U.S. regulators and internal or external audits
  • Collaborate with model development, audit, and other internal partners
  • Provide structural feedback to business and first-line stakeholders
  • Report to the Senior Manager, Advanced Analytics – Liquidity Risk Management Model Validation

Requirements

What you’ll need
  • Advanced quantitative skills with a post-secondary degree in Statistics, Economics / Econometrics, Mathematics, Finance, Financial Engineering, or Financial Risk Management
  • 1–2 years of work experience in model development or model validation in a financial institution
  • Experience developing AI agent workflows to increase productivity
  • Strong technical knowledge and proficiency in Python, SQL, SAS, and VBA
  • Hands-on experience developing and implementing statistical forecasting models, such as time-series models
  • Solid knowledge of financial products and portfolios, including cash flow patterns and pricing / valuation approaches
  • Strong technical writing and excellent verbal communication skills
  • Strong analytical and problem-solving skills
  • High attention to detail
  • Good time management and multitasking skills with minimal supervision
  • CFA / FRM charter holder or candidate preferred
  • Qualification in data risk management or operational risk management is an asset
  • Experience in business system analytics or developing / validating large banking treasury reporting systems is an asset
  • Risk management experience is an asset
  • Familiarity with JSON and Scala is an asset
  • Familiarity with data pipeline processes, banking data infrastructure, and data control & governance is an asset
  • Inquisitive nature and ability to ask appropriate questions and escalate issues
  • Risk and control mindset with good business acumen is an asset

Benefits

Comp & perks
  • Base salary
  • Variable compensation
  • Health and well-being benefits
  • Savings and retirement programs
  • Paid time off
  • Banking benefits and discounts
  • Career development
  • Reward and recognition programs
  • Regular development conversations
  • Training programs
  • Online learning platform
  • Mentoring programs
  • Training and onboarding sessions
  • Interview accommodations, including accessible meeting rooms and captioning for virtual interviews