Director, Climate Analytics and Solution Enablement

Job Description

What is the Opportunity?

Reporting to the Senior Director, Climate in the Chief Data Office, the Director will be responsible for leading a team through the design and delivery of advanced and foundational analytics solutions that enable RBC to deliver on its climate and enterprise strategic priorities. Your team will develop and implement models and data-driven solutions that power key metrics and enable high-impact use cases across our lines of business.

This role goes beyond technical execution. It is a rare opportunity to operate at the intersection of data science, strategy, and enterprise transformation—building decision-enabling solutions that drive RBC’s climate and sustainability ambition. You'll be working with executives, business leaders, and technical teams to turn complex modeling into business-ready solutions, with the autonomy to shape how analytics unlock new value pools across RBC.

• Oversee a portfolio of analytics projects that power high-stakes outputs including strategic products (internal & external facing), executive scorecards, sustainability disclosures, and regulatory filings.
• Lead the development, validation, enhancement, and implementation of traditional and advanced models (e.g., LLMs, neural networks, and structured methods) supporting RBC’s climate and strategic priorities in accordance with enterprise risk management policies.
• Translate uncertain, complex and evolving business and regulatory requirements into robust analytics solutions with tangible business value.
• Integrate models as core elements of analytics products used across the enterprise.
• Collaborate with cross-functional teams across our lines of business and functions to ensure alignment and execution.
• Communicate clearly and persuasively with stakeholders, especially through crisp, insight-rich presentations and executive briefings.
• Manage and coach a high-performing team of quantitative professionals, fostering innovation, growth, and delivery excellence.
• Stay at the forefront of external best practices, modeling methodologies, and sustainability data trends, interfacing directly with external stakeholders (e.g., peers, PCAF/CBA working groups)

• Experience leading advanced analytics/modeling initiatives in fast-paced, high-visibility environments.
• Demonstrated ability to embed models into business-facing tools or digital products to drive real-world outcomes.
• Proficiency in Python, SQL, and contemporary data science and analytics technologies.
• Excellent communication skills with a strong ability to simplify and synthesize complexity for executive and non-technical audiences.
• Proven leadership of cross-functional projects or teams with multiple stakeholders.

• Master’s or PhD in a quantitative, technical, or interdisciplinary discipline (e.g., Statistics, Financial Engineering, Applied Mathematics, Climate Science, Computer Science).
• Experience in consulting or enterprise strategy roles, especially within data, sustainability, or finance domains.
• Familiarity with climate and sustainability metrics (e.g., financed emissions, scenario modeling, transition alignment) and the foundational methodologies that underpin these metrics (e.g., PCAF, GHG Protocol).
• Familiarity with scenario modelling (e.g., IEA NZE, IPCC RCP/SSP, NGFS).
• Experience developing or governing analytics solutions in enterprise technology or cloud environments.

• A leadership opportunity to shape how RBC uses analytics to drive its sustainability and enterprise agenda.
• Direct influence on decision-making at the highest levels of the bank.
• Ability to build new products and practices with executive sponsorship and organizational visibility.
• A collaborative culture that values innovation, experimentation, and impact.
• Competitive compensation, flexible benefits, and strong professional development pathways.

Artificial Intelligence (AI), Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language), Statistical Analysis

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