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Scrum Master - Finance Data Delivery Manager – Analytics, Insights & Artificial Intelligence

Job in Toronto, Ontario, C6A, Canada
Listing for: TD
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems/ Tech Analyst, Data Science Manager, AI Engineer
Salary/Wage Range or Industry Benchmark: 96900 - 136800 CAD Yearly CAD 96900.00 136800.00 YEAR
Job Description & How to Apply Below

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Line Of Business: Enterprise Enabling Functions

Pay Details: $96,900 - $136,800 CAD

This role is eligible for a discretionary variable compensation award that considers business and individual performance.

Job Description Build the future of Finance Data & AI delivery

We’re looking for a high‑impact Scrum Master / Finance Data Delivery Manager to help accelerate Finance’s data, analytics, and artificial intelligence agenda. This role sits at the intersection of Agile delivery, finance transformation, and emerging technology
, enabling teams to deliver meaningful outcomes in a complex, regulated environment.

If you thrive on removing obstacles, aligning stakeholders, and helping teams deliver high‑quality data and AI solutions at scale, this is an opportunity to make a real enterprise impact.

What You’ll Do Agile & Delivery Leadership
  • Serve as Scrum Master and Delivery Manager for Finance Data, Analytics, and AI initiatives
  • Champion Agile and Lean practices aligned to enterprise delivery standards
  • Facilitate all Agile ceremonies including sprint planning, stand‑ups, reviews, retrospectives, and PI planning
  • Enable high‑performing, self‑organizing teams while fostering psychological safety and shared accountability
  • Drive continuous improvement through delivery metrics, insights, and retrospectives
Finance Data, Analytics & AI Delivery
  • Lead delivery of strategic finance data and analytics initiatives, ensuring alignment to business priorities
  • Support AI and advanced analytics programs, including iterative experimentation, model development, and deployment workflows
  • Work with Stakeholders to translate complex data and AI work into clear, value‑driven Agile increments
  • Navigate ambiguity inherent in emerging technologies while maintaining delivery discipline
  • Manage cross‑team dependencies, risks, and impediments across data and technology work streams
Stakeholder & Governance Partnership
  • Partner closely with Product Owners, pillar leads, and executive stakeholders to define and prioritize backlogs and roadmaps
  • Align delivery execution with finance data strategy, governance models, and regulatory requirements
  • Support delivery controls, checkpoints, and reporting in a risk‑ and control‑focused environment
  • Ensure transparency, accountability, and timely escalation of delivery issues
What You Bring Core Experience
  • Proven experience (minimum 6 years) as a Scrum Master, Agile Delivery Lead (not just participating on Agile teams)
  • Strong working knowledge of Scrum, Kanban, and scaled Agile frameworks (e.g., SAFe)
  • Experience with hands‑on facilitation of all core Agile ceremonies (planning, stand‑ups, reviews, retrospectives, PI planning)
  • Demonstrated success delivering finance, data, analytics, or transformation initiatives in a large organization
  • Experience of operating in financial services or other regulated environments
  • Ability to deliver against strategic roadmaps, not just isolated projects
  • Ability to translate complex finance, regulatory, or data concepts into clear visual narratives (Use of PowerPoint/ Power BI etc.). Experience building executive‑ready decks, decision briefs, and transformation updates with a strong sense of visual design (clean layouts, appropriate charts, consistent formatting, clarity of message)
  • Preferred experience with artificial intelligence (AI) applications in finance data, including the use of Python and SQL for data analysis, automation, and insight generation.
  • What is NOT required
  • Deep coding expertise (Python/SQL are exposure‑level, not core)
  • Hands‑on model development
  • Technical architecture ownership
  • People‑manager responsibilities
Analytics & AI Exposure
  • Experience supporting delivery of data platforms, analytics, AI, or machine learning initiatives
  • Familiarity with governance, controls, and lifecycle considerations for analytics and AI solutions
  • Ability to bridge conversations between business, data, and technology teams
  • Experience supporting AI, ML, or advanced analytics initiatives
  • Familiarity with iterative experimentation, model lifecycle checkpoints, or AI governance concepts
  • Ability to translate complex analytics work into Agile increments
Skills &…
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