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.