Corporate Vice President - Financial Modeling Technology

New York Life•New York, NY

1d•$185,000 - $264,500•Hybrid

About The Position

The Corporate Vice President, Financial Modeling Technology provides senior technology leadership for a major domain within New York Life's Enterprise Plan to Perform (EPP) transformation. The initial assignment is Financial Modeling, where the leader will own the technology ecosystem supporting critical financial models and analytical capabilities, including Capital Planning, NII Modeling, Driver-Based Modeling, and Scenario Analysis. The role owns the end-to-end technology capability for the domain, spanning technology strategy, roadmap, applications, data and analytics requirements, AI and automation, architecture, integration, engineering, controls, production readiness, workforce and partner capacity, and measurable business outcomes. The leader works across Finance, business, Technology, Data, Architecture, Risk and Control functions, and strategic partners to translate future-state business intent into scalable enterprise capabilities. This is broader than an application development or program management role. The leader is expected to combine business understanding, systems thinking, technology and engineering judgment, and transformation leadership; challenge current-state constraints; and ensure the domain evolves as a coherent capability that integrates effectively with the broader EPP ecosystem and NEXUS experience.

Requirements

15+ years of progressively responsible experience in technology, software engineering, solution delivery, digital transformation, or related disciplines, including significant leadership responsibility in complex enterprise environments.
Proven experience owning end-to-end technology capabilities or major transformation domains from strategy through architecture, engineering, implementation, and measurable outcomes.
Demonstrated success operating in federated or matrixed enterprises and influencing senior business and technology stakeholders across organizational boundaries.
Broad technology and engineering background spanning modern application development, APIs and integration, data and analytics, cloud platforms, enterprise architecture, automation, and emerging technologies.
Strong understanding of generative AI, agentic technologies, and AI-assisted engineering and their practical application to enterprise workflows and software delivery.
Experience leading multidisciplinary technology teams and managing strategic partners, contractors, and federated resources.
Experience operating within enterprise Risk, Security, Compliance, Audit, and control environments.
Strong analytical, communication, prioritization, and executive-influence capabilities.
Domain Technology Leadership - Owns the complete technology capability for a major business domain, not simply an application portfolio.
Technology & Engineering Judgment - Evaluates solution approaches, architecture and data implications, engineering tradeoffs, and production risks.
Systems Thinking - Understands interactions across process, applications, data, analytics, architecture, controls, and operating models.
AI-Enabled Transformation - Identifies where AI and agentic capabilities can materially change workflows, decisions, and delivery economics.
Executive Communication & Influence - Creates clarity, drives decisions, and influences senior stakeholders across organizational boundaries.
Strategic Planning & Execution - Converts future-state ambition into prioritized roadmaps, investments, sequencing, and executable outcomes.
Enterprise Delivery Discipline - Applies SDLC, Agile and Lean principles pragmatically with strong dependency, release, and production-readiness management.
Talent & Partner Leadership - Builds strong teams and integrates internal, federated, and external engineering capacity around common outcomes.
People Management – Develops and empowers talent through clear expectations, actionable feedback, effective coaching, and accountability, while fostering an inclusive, high-performing team environment.

Nice To Haves

Experience with financial modeling platforms, calculation engines, actuarial or finance models, capital/NII modeling, scenario analysis, or quantitative technology.
Experience with model governance, reproducibility, lineage, controls, and integration of complex models into enterprise workflows.

Responsibilities

Own the future-state technology capability across Capital Planning, NII Modeling, Driver-Based Modeling, Scenario Analysis, and related financial modeling capabilities.
Modernize modeling architecture to improve scalability, transparency, reproducibility, explainability, reuse, and integration with enterprise planning and decision support.
Lead distinct outcome teams for Capital Planning, NII Modeling, Driver-Based Modeling, Scenario Analysis, and additional modeling capabilities as the domain evolves.
Establish robust patterns for model inputs, calculation engines, versioning, lineage, controls, testing, model outputs, and integration into downstream planning and performance experiences.
Evaluate where AI can accelerate model development, scenario generation, explanation, sensitivity analysis, and user interaction while preserving deterministic calculations and appropriate controls.
Own the target-state technology strategy and roadmap for the domain, including application, integration, data, analytics, AI, automation, and engineering implications.
Drive pragmatic use of rapid prototyping, specification-driven development, AI-assisted engineering, automated testing, and continuous business validation.
Promote systems thinking so solution decisions account for upstream and downstream impacts across workflows, data, architecture, security, controls, and operations.
Identify where generative AI and agentic capabilities can materially reimagine workflows, analysis, decision support, and execution rather than simply automate existing steps.
Maintain strong standards for engineering quality, scalability, resiliency, responsible AI, observability, production readiness, and technical sustainability.
Partner closely with Planning & Projections Technology so models are embedded in planning and forecasting workflows rather than operating as isolated analytical assets.
Partner with NEXUS Technology to surface model outputs, scenarios, explanations, and decision support through the common EPP experience.
Partner with Data Architecture on authoritative inputs, lineage, semantics, and traceability required for controlled financial modeling.
Partner with Business Discovery & Solution Strategy leaders to translate future-state business intent into executable technology capabilities and roadmaps.
Partner with Solution Engineering & Architecture and Data Architecture to ensure domain solutions align with cross-EPP architecture and data patterns.
Lead multidisciplinary outcome teams and coordinate NYL engineers, forward deployed engineers, federated resources, domain SMEs, and strategic partner engineers.
Build trusted relationships with senior Finance, business, and Technology stakeholders and create transparency around priorities, tradeoffs, risks, dependencies, and outcomes.
Shape domain investment priorities, sequencing, resource requirements, and capacity plans based on business value, dependencies, risk, and delivery readiness.
Manage strategic technology and engineering partners as an integrated part of the domain team with clear accountability for quality, outcomes, and knowledge transfer.
Establish transparent measures of delivery health, adoption, quality, and value realization and use them to drive decisions and accountability.
Ensure security, privacy, controls, auditability, and operational readiness are incorporated from inception through production.
Build, lead and develop high performing teams with strong domain knowledge and modern technology and engineering capabilities.
Attract, develop and retain forward deployed and other high caliber technology talent, while building technology leadership and domain expertise across the organization.
Establish clear accountability and a culture of collaboration, innovation, engineering discipline and continuous improvement.
Lead effectively through both direct authority and matrixed relationships across Business, Product, Technology and partner teams.