Data Analytics and AI VP

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

We are seeking a Vice President to join the Portfolio and Execution Management function within the Business Enablement and Transformation team. 

As a VP, you will lead the evolution of Infrastructure Platforms' data and decision intelligence capabilities, enabling faster, more informed and more proactive decision-making across portfolio management, investment governance and strategic execution. Leveraging advanced analytics, automation and approved AI-enabled solutions, the role will transform how leaders understand portfolio health, prioritize investments, identify risk and drive execution outcomes.

Job responsibilities:

• Developing data solutions to support business and management reviews and decision forums. Structuring analytics to identify potential opportunities for enterprise change and improvement.
• Design and implement AI-enabled decision-support solutions that leverage machine learning, predictive analytics and generative AI techniques to improve portfolio prioritization, investment governance and execution outcomes and surface trends, risks, anomalies and recommended actions. 
• Leveraging data visualization and data transformation tools to build impactful dashboards for leadership and IP stakeholders.
• Partner with technology, product, risk and controls stakeholders to ensure AI-enabled reporting and automation use appropriate human review, data lineage, access controls and transparent assumptions. 
• Help define reusable analytics patterns, prompts, metrics definitions and reporting standards so insights are consistent, auditable and scalable across IP stakeholders.
• Working with stakeholders and subject matter experts on requirements for key business metrics, data sourcing, visualization, and publishing. 

• Independently managing multiple efforts simultaneously across a range of domains.

Required qualifications, capabilities and skills:

• 8+ years of hands-on experience developing analytical solutions in a fast-paced environment (preferably financial services) and/or experience in management consulting with a heavy emphasis on quantitative analysis.
• Thrive in a fast-paced, high-impact environment—ability to prioritize ruthlessly, and making disciplined trade-offs to deliver high-quality outcomes in a dynamic environment.
• Demonstrated problem-solving and issue identification skills, along with the ability to structure ambiguous problems and synthesize quantitative and qualitative inputs into clear recommendations.
• Interpersonal leadership and influencing skills. Proven stakeholder management skills and ability to influence across a matrix.
• Bachelor’s Degree (or higher) in a quantitative discipline (e.g. Computer Science, Engineering, Applied Statistics, Mathematics or similar)
• Strong experience with enterprise data ecosystems, including SQL, APIs, cloud-based data platforms, data modeling and data integration architectures. Ability to build and scale reusable data products, analytic assets and self-service decision-support capabilities. 
• Experience leveraging Generative AI, LLM-based solutions, Copilot technologies, retrieval-augmented generation (RAG), AI-assisted analytics platforms or similar enterprise AI capabilities.
• Familiarity with infrastructure and cloud technology a plus, e.g., datacenter compute, storage, database, network, mainframe, middleware a plus
• Strong creative problem-solving skills. Ability to set goals, prioritize and manage across complex workstreams, and drive thinking and progress proactively and independently.
• Comfort with ambiguity, including the application of skills within new and unfamiliar domains. Demonstrated ability to communicate complex analytical insights and AI-driven recommendations to senior executives and influence strategic decisions.
• The successful candidate will be expected to use AI responsibly, applying sound judgment, human oversight, transparency, data-quality discipline and appropriate controls when developing AI-assisted analytics, automation and executive reporting capabilities.