Corporate Vice President - Data Science Lead

New York Life Insurance Co•New York, NY

7d•$147,500 - $211,000•Hybrid

About The Position

As part of the Artificial Intelligence & Data (AI&D) organization, you will contribute to New York Life’s AI-led transformation by developing and supporting the deployment of AI and Machine Learning solutions that enhance efficiency, enable a seamless customer experience, and improve client, agent, and employee experiences, delivering unparalleled value as the firm continues to become tech, data, and AI enabled. This role will support the development of AI solutions spanning traditional Machine Learning, Generative AI, and Agentic AI, while also providing technical leadership through mentoring junior data scientists and interns, supporting their growth and development. You will work in close partnership with business product owners to champion new ideas that advance AI adoption, while helping measure, articulate, and communicate business value. You will collaborate closely with business stakeholders, data scientists, engineers, and product and technology partners, contribute to hiring decisions for full-time employees, interns, and contractors, and continue to build expertise in enterprise AI practices, model lifecycle management, responsible AI principles, and New York Life’s technology ecosystem.

Requirements

Advanced degree in Computer Science, Data Science, Machine Learning, AI, Engineering, Mathematics, Statistics, or a related quantitative field.
8+ years of experience applying data science and AI/ML to real-world business problems.
2+ years of experience working with business stakeholders for delivering on the key roadmap initiatives.
Ability to communicate complex ideas simply, presenting impact, trade-offs, and recommendations to non-technical partners.
Proficiency in Python and SQL; working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging).
Solid experience with cloud platforms like AWS/GCP services (e.g., SageMaker, Bedrock, Vertex AI) and modern data ecosystems (Snowflake/Databricks).
Working knowledge of LLMs, RAG architecture, and agentic frameworks, including safe automation design and evaluation practices.
Solid grounding in ML methods (supervised and unsupervised learning, gradient boosting, exposure to deep learning), feature engineering, regularization, cross-validation.
Ability to translate analytical findings into clear business insights and collaborate effectively with cross-functional partners. Translate them into an overall AI roadmap.
Experience collaborating across product, data, and engineering teams to deliver scalable, production-ready AI solutions.

Nice To Haves

Experience in Life Insurance industry or consumer finance domains is a plus.

Responsibilities

Lead the execution of AI/ML and GenAI initiatives in partnership with data, technology, product, and business teams to deliver scalable solutions
Partner with tech and business lead to redesign and operationalize business workflows that embed the AI, GenAI and Agentic solutions.
Own business-aligned OKRs for AI initiatives, ensuring efforts are outcome-driven, tied to enterprise value creation and supported through PI planning and roadmap development.
Deliver all aspects of full Model Development Life Cycle (MDLC) from data exploration and feature engineering to model training, validation, deployment, and performance monitoring.
Develop and help operate models using cloud platforms (e.g., AWS, GCP) and modern data platforms (Snowflake, Databricks), ensuring quality, security, and scalability, partner with ML engineers for large-scale production deployment and scaling.
Implement and refine LLM/RAG approaches (vector stores, embeddings, retrieval optimization, prompt orchestration) with evaluators for reliability.
Adhere to model governance, documentation, testing, and CI/CD best practices in partnership with MLOps.
Mentor and hire junior data scientists, interns and vendor resources to deliver key business initiatives.
Assist in designing and evaluating agentic/AI-powered solutions that automate routine business tasks with human-in-the-loop checkpoints, escalation thresholds, and safety guardrails.
Work with AI Engineers to ensure AI capabilities are accessible through APIs, dashboards, and integrated workflow applications used by business teams.
Build lightweight UI prototypes (e.g., Streamlit) to validate usability and support adoption.
Stay informed on industry trends by engaging in relevant conferences and sharing key insights with internal and external audiences as appropriate.
This role involves limited travel (<10%) to events and vendor meetings.