Senior Manager, GTO Strategy & Transformation

In this role, you will support execution of GTO's strategy, transformation, AI enablement, workforce modernization, value realization, and governance agenda. You will conduct deep operational and business analysis, develop business cases, support executive decision-making, and help ensure transformation initiatives produce measurable outcomes across Technology and Operations. You will serve as a key coordination point across 14 countries, maintaining visibility across portfolio priorities and supporting timely execution, while also enabling Tech and Operations teams — who are increasingly building and owning AI models through low-code/no-code and vendor solutions — to understand and fulfill their first-line Model Risk Management obligations. This is an AI-native team — you will use AI tools, agentic workflows, and LLM-connected platforms as your primary way of working, not as an occasional add-on.

Position Responsibilities:

• •Operational Analytics & Diagnostics: Conduct deep-dive, multi-year performance analysis across GTO segments and functions to identify root causes of performance shifts and quantify improvement opportunities — spanning operational metrics (e.g., volume, containment, service level, workforce trends), technology delivery metrics, and financial/benefit data, depending on the initiative. Reconcile findings across multiple data sources, flagging discrepancies and data-quality issues rather than presenting unverified figures. Build reusable analytical frameworks (e.g., target-setting waterfalls, seasonality-adjusted projections, business-case models) that leadership can rely on for decision-making across current and future transformation priorities — contact centre performance is one current application of this capability, not its definition.
• •Business Case Development & Value Realization: Build quantified business cases, validate assumptions, reconcile benefits, support investment prioritization, and track transformation outcomes. Ensure benefit claims remain defensible against source data as initiatives move from proposal through delivery.
• •Transformation Planning & Execution: Support delivery of GTO transformation initiatives through roadmap development, milestone tracking, dependency management, and executive reporting.
• •Executive Decision Support & Strategic Communications: Produce competitive benchmarking, landscape analysis, and strategic briefings to support AVP and Director decision-making. Synthesize complex information — regulatory developments, market signals, internal performance data — into clear, executive-ready formats, including anticipated-question briefs ahead of ELT and Board/Technology Committee sessions, Board and investor-facing content, and strategic storyline development. This is one of the highest-leverage and most defining parts of the role — the quality of this synthesis directly shapes senior leadership's understanding of GTO's transformation progress.
• •Operating Model & Workforce Analysis: Analyze workforce trends, process changes, productivity opportunities, and future-state operating models to support AI-enabled transformation initiatives.
• •Responsible AI Governance: Lead evidence coordination and governance pipeline management for AI initiative reviews. Work credibly and independently with Risk, Legal, Compliance, and Privacy partners — ensuring clearance without stalling delivery. Own the end-to-end governance intake pipeline, flag blockers early, and maintain accurate documentation aligned to enterprise standards including OSFI E-23 and privacy frameworks.
• •Model Risk Management Enablement: As Tech and Operations teams increasingly own AI models built through low-code/no-code tools and vendor solutions, provide guidance and subject matter expertise to model owners on their first-line MRM obligations. Support teams in preparing and submitting required documentation — model cards, risk tiering assessments, methodology documentation, and monitoring plans — and assist them in maintaining ongoing obligations including review cycles, change notifications, and performance reporting. Accountability for model risk remains with the designated model owner in Tech or Operations.
• •Global Coordination: Maintain the operational rhythm across 14 countries — intake tracking, reporting cadence, escalation management, and cross-country knowledge sharing. Ensure the AVP and Director have timely, accurate visibility across portfolio priorities and emerging issues.
• •Regulatory Navigation: Interpret and operationalize regulatory requirements — OSFI E-23, privacy impact assessments, cross-border data residency, model risk guidance — into actionable delivery guidance for AI teams across segments and countries.
• •Target & Benefit Tracking: Support target setting and own benefit realization tracking across the portfolio, including operational transformation initiatives. Surface variances early, distinguish transformation-driven improvement from organic trends, coordinate resolution, and maintain accurate progress reporting for senior leadership and ELT.
• •Workforce Transformation Execution Support: Monitor AI reskilling and workforce pathway program execution across Tech and Operations segments. Track progress against commitments, identify gaps, and escalate issues to the AVP and Director to support timely resolution.
• •Reporting & Communications: Prepare ELT and SteerCo inputs, portfolio dashboards, and initiative status summaries. Maintain documentation standards and traceable evidence trails aligned to enterprise audit and governance requirements.
• •AI-Augmented Delivery: Apply AI tools and agentic workflows directly to the team's day-to-day output. Use LLMs connected to enterprise data platforms and AI platforms to reimagine how portfolio reports, operational diagnostics, strategy documents, and executive presentations are built — moving from manual production to intelligent, repeatable workflows, including direct querying and reconciliation of live operational data. Establish and share these patterns across the team, and maintain a living knowledge base of methodology, findings, and reusable analysis patterns to accelerate future work.
• •Continuous Improvement: Identify and implement process improvements across governance workflows, MRM documentation processes, analytics methodology, and coordination mechanisms. Improve templates, checklists, and guidance to reduce rework and accelerate cycles without compromising rigor.

Required Qualifications:

• •Experience supporting enterprise strategy, operating model design, transformation programs, or value realization initiatives.
• •Demonstrated experience in operational/business analytics — working directly with enterprise data (SQL, data platforms such as Databricks, or equivalent) to diagnose performance trends, validate findings across multiple sources, and produce decision-ready analysis for senior stakeholders.
• •6+ years of experience across strategy, transformation, AI governance, model risk management, compliance, operational risk, or technology risk, preferably in a regulated financial services environment.
• •Demonstrated experience supporting or coordinating first-line model risk obligations — including model inventory management, risk tiering, documentation requirements, and ongoing monitoring commitments.
• •Demonstrated experience in Responsible AI governance, including ownership of governance reviews, working knowledge of OSFI guidelines and privacy frameworks, and the ability to lead evidence coordination independently.
• •Practical understanding of AI/ML risks — bias/fairness, explainability, robustness, data privacy — and how governance requirements translate into delivery evidence.
• •Ability to communicate complex analysis and MRM obligations clearly and accessibly to non-specialist stakeholders across Tech and Operations teams.
• •Strong organizational and coordination skills; comfortable managing multiple concurrent workstreams across global teams