Lead Data Scientist, Corporate Vice President | New York, NY

and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture. The Center for Data Science and Artificial Intelligence (CDSAi) is the 70-person innovative corporate Analytics group within New York Life.

We are a rapidly growing entrepreneurial department which designs, creates, and offers innovative data-driven solutions for many parts of the enterprise. For more information on CDSAi, please visit our website (/careers/corporate/data-science). We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a whole

new generation of predictive analytics and artificial intelligence solutions. In the 7 years of the existence of CDSAi we have built a lot of predictive modeling solutions that are being used by various areas in the company.

We have also stood up a modern model deployment platform that allows our models to be accessed in real time or batch (via APIs) from any production system in the company. In addition to several data science teams, CDSAi has a dedicated ML Ops team (for all infrastructure, data and model deployments), our own project management office, a model governance team, a development team (training, internships, media, events, other internal and external branding) and data science

product managers. CDSAi closely supports core business areas such as Underwriting, Marketing, Sales, Finance and Service.

This specific role is focused on building out the data science support function for the Strategic Businesses, which include: Group businesses (group benefits and group membership) Institutional businesses (annuities and life) Insurance business in Mexico The data scientist who fills this role will benefit from both the stability and support of being on an established data science team AND the exciting challenge of building out a new analytics area. The role reports to Mary M. Louie ( /in/mary-louie-a25706125/ ), who currently leads the Strategic Businesses (SBs) Data Science team.

A good understanding of predictive analytics (including the process of building and deploying models) and technology is essential. Examples of SB Data Science products are below. There are several additional ones, and more products will follow. Mortality assumptions modeling in support of Pension Risk Transfers Group disability claims scoring and triaging. Forecasting productivity for agents While this position requires expert-level familiarity with regular statistical predictive modeling methodologies and practice, the data scientist will also have opportunities to work on generative AI projects and initiatives.

NYL’s CEO has expressed that he wants the company to be a leader in generative AI in our industry. This role will have the opportunity to help build out that vision. Responsibilities Managing various stakeholders at the same level during solution design and project execution to successfully create solutions and deploy them into full production. Independently leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.

Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits. Provides technical support, which includes strategic consulting, needs backssments, project scoping and the preparation/presentation of analytical proposals. Utilizes advanced statistical/AI techniques to create high-performing predictive models and other solutions to address business objectives and client needs. Tests new statistical and machine learning methods, software and data sources for continual improvement of quantitative solutions.

Implements analytical models into production by collaborating with technology and ML Ops teams. Utilizes data visualization tools for model testing, modeling results and data patterns exhibition. Design performance metrics for model selection and performance monitoring. Utilizes data wrangling/data matching/ETL techniques while programming in several languages to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets.

Deploys analytical solution in production systems. Works closely with the business areas, IT, Legal, Government relations and several other groups in designing, building, and implementing these solutions. Evangelizes the use of data-based decision making and Analytics within New York Life. Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with internal clients and stakeholders on project/test results, opportunities, questions.

Resolves problems and removes obstacles to timely and high-quality project completion. Works collaboratively with project and product managers within CDSAi and on other teams. Supports and helps build a generative AI practice within CDSAi. Supports internal events, expos, lunch & learns, etc. with displays and presentations. Follows industry trends in insurance and related data/analytics processes and businesses. Functions as the analytics expert in meetings with other internal areas and external vendors. Contributes ideas and actively participates in proof-of-concept tests of new processes and technologies.

Stays up to date on existing and proposed legislation and regulation (on federal and state level) that impact AI in underwriting. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects. Travels to events and vendor meetings as needed (