Job Description:

Location Designation: Hybrid - 3 days per week 

 

 

When you join New York Life, you’re joining a company that values career development, collaboration, innovation, and inclusiveness. We want employees to feel proud about being part of a company that is committed to doing the right thing. You’ll have the opportunity to grow your career while developing personally 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 Head of AI Center of Excellence will play a pivotal role in leading and expanding our generative AI and advanced machine learning capabilities. Collaborating closely with the Head of ML Ops, this leader will be responsible for building a cutting-edge generative AI practice and associated assets. The ideal candidate will have substantial experience in developing and deploying generative AI and advanced machine learning solutions and will also possess the ability to attract top talent with similar skill sets.  

 

This role offers a unique opportunity to help shape the company’s vision of becoming a leader in generative AI within our industry, as emphasized by NYL’s CEO. 

In addition to generative AI, the role requires deep expertise in traditional statistical predictive modeling, as not every project will necessitate generative AI. The Head of AI Center of Excellence will report to the Chief Data Science Officer at New York Life. 

 

Key Responsibilities: 

* Lead the Generative AI Practice: Build and manage the generative AI practice within the AI Team, including developing use cases and managing stakeholders across various business units. This also involves talent acquisition and development, advocating for advanced problem-solving techniques, and ensuring proper infrastructure and tooling in collaboration with ML Ops and IT. 

* Collaborate Across the Organization: Work with analytics leaders’ company-wide to address complex problems, drive innovation, and enhance team structures and organization. 

* Stakeholder Management: Oversee the design and execution of AI solutions, ensuring successful deployment into full production while managing diverse stakeholders throughout the process. 

* Thought Leadership: Serve as a thought leader and consultant on AI at the enterprise level, providing strategic insights and guidance. 

* Support Corporate AI Initiatives: Contribute to AI workstreams and enterprise-wide initiatives, offering support to corporate functions. 

* Promote Organizational Effectiveness: Demonstrate strong storytelling and product branding skills, which are as crucial as technical leadership within a complex organization like NYL. 

* Advanced AI and ML Techniques: Utilize cutting-edge statistical, machine learning, and AI techniques to develop high-performing models and solutions that meet business objectives. Continuously test new methods and technologies for ongoing improvement. 

* Facilitate Model Production: Collaborate with technology and ML Ops teams to transition models into production and enhance MLOps practices. 

* Data Visualization and Tools: Employ visualization tools for model testing, results presentation, and data pattern analysis. Design metrics for model selection and performance monitoring. 

* Team Leadership: Build, manage, and retain a team of highly skilled data scientists. This includes goal setting, performance evaluation, resource allocation, career development, and recruitment. 

* Develop New Use Cases: Explore, design, and gain approval for new data science use cases. Create strategies and project pipelines, leveraging the opportunities within NYL's size and complexity. 

* Cross-Functional Collaboration: Work closely with business areas, IT, Legal, Government Relations, and other groups to design, build, and implement AI solutions. 

* Advocate for Data-Driven Decisions: Promote the use of data-driven decision-making and analytics across New York Life. 

* Effective Communication: Communicate clearly and effectively with internal stakeholders, partners, and clients on product design, data specifications, model implementations, and project outcomes. Resolve issues and remove obstacles to ensure timely and high-quality project completion. 

* Collaborate with Project Managers: Work closely with project and product managers within AI & Data and across other teams to ensure successful project execution. 

* Support Internal Events: Participate in and support internal events, expos, and lunch-and-learns with presentations and displays. 

* Stay Informed on Industry Trends: Keep up with industry trends in insurance and related data/analytics fields, functioning as an analytics expert in internal and external meetings. Actively contribute to proof-of-concept tests for new processes and technologies. 

* Ensure Compliance: Stay updated on relevant legislation and regulations affecting AI in underwriting. Ensure compliance with regulatory and privacy requirements during the design and implementation of AI projects. 

* Travel: Attend events and vendor meetings as needed (