Corporate Vice President, Financial Modeling Technology – Financial Modeling

Job Description

Corporate Vice President – Financial Modeling Technology | New York Life Insurance Company

The Tone:
This is a full-time role at New York Life Insurance Company, with a hybrid designation requiring 3 days per week in the office, typically in New York, New York, USA. The company’s Tech, Data, AI, and Ventures (TDAV) organization leverages technology, data, and AI to build solutions that accelerate competitive advantage and serve policy owners, agents, advisors, and employees. This role is pivotal in leading the technology ecosystem for critical financial models within the Enterprise Plan to Perform (EPP) transformation, modernizing financial planning and performance management for a world-class financial services company.

The TL;DR
• Role: Full Time
• Type: Full Time
• Location: Hybrid – New York, New York, USA
• Pay: $185000–$264500 yearly
• Team: Enterprise Plan to Perform (EPP) within the Tech, Data, AI, Ventures (TDAV) organization
• Mission: Own the end-to-end technology capability for financial modeling, transforming how the enterprise plans, projects, understands, and manages financial performance using modern technology, data, analytics, automation, and AI.
• Tech Stack: Modern application development, APIs, integration, data and analytics, cloud platforms, enterprise architecture, automation, generative AI, agentic technologies, AI-assisted engineering, rapid prototyping, specification-driven development, automated testing

What You’ll Actually Do
• Domain Technology Strategy & Ownership: Own the future-state technology capability across Capital Planning, NII Modeling, Driver-Based Modeling, and Scenario Analysis, modernizing its architecture for scalability, transparency, and integration.
• AI & Engineering Leadership: Drive the target-state technology strategy and roadmap, leveraging AI-assisted engineering, automated testing, and generative AI to reimagine workflows and maintain high engineering quality.
• Cross-Functional Leadership: Partner with Finance, business, and other Technology teams (Planning & Projections, NEXUS, Data Architecture) to translate business intent into executable capabilities and ensure effective integration across the EPP ecosystem.
• Delivery & Investment Accountability: Shape domain investment priorities, manage strategic technology partners, and establish transparent measures for delivery health, quality, and value realization, ensuring security and operational readiness.
• Talent & Organizational Leadership: Build, lead, and develop high-performing multidisciplinary teams, attracting and retaining top technology talent, and fostering a culture of collaboration, engineering discipline, and continuous improvement.

The Must-Haves
• Background: Executive-level technology leadership in complex enterprise environments, digital transformation, software engineering, or solution delivery.
• Experience: 15+ years of progressively responsible experience, including proven success owning end-to-end technology capabilities or major transformation domains, operating in federated/matrixed enterprises, influencing senior stakeholders, and leading multidisciplinary teams while managing strategic partners.
• Skills: Domain Technology Leadership (owning complete technology capability for a major business domain), Technology & Engineering Judgment (evaluating solution approaches, architecture, engineering tradeoffs, and production risks), Systems Thinking (understanding interactions across process, applications, data, analytics, architecture, controls, and operating models), AI-Enabled Transformation (identifying where AI and agentic capabilities can materially change workflows, decisions, and delivery economics), and Executive Communication & Influence (creating clarity, driving decisions, and influencing senior stakeholders).
• Bonus: Experience with financial modeling platforms, calculation engines, actuarial/finance models, capital/NII modeling, scenario analysis, or quantitative technology, including model governance, reproducibility, lineage, controls, and integration of complex models into enterprise workflows.