Direct Summer Internship Program - AI & DS

Shape Your Future

Shape your future with a dynamic internship experience at New York Life. Your internship journey is designed to challenge you through hands-on work experience that will equip you with valuable skills you can use anywhere. You will build your network through collaboration and connection with talented interns and experienced employees through team-building activities, mentorship programs, and fun social events. By the end of your internship, you'll be equipped with new skills and a network that will propel you forward in your career journey.

Beginning in June and ending in August, this 10-week summer internship is part of the New York Life Direct (NYLD) program, the industry leader in direct-to-consumer life insurance. NYLD delivers streamlined life insurance solutions directly to individuals, bypassing traditional agent models.

As an Advanced Analytics (Data Science) Intern, you will be a member of the Advanced Analytics team, supporting data-driven decision-making across the business. The program offers valuable professional development through practical experience, exposure to senior leaders, and collaboration across functions including Finance, Marketing, Product, Research and Underwriting Strategy, Technology, Actuarial, and Insurance Operations.

The intern will also gain exposure to how modern artificial intelligence, machine learning, and generative AI tools can be applied responsibly to analytics workflows and business problems. This role follows a hybrid work model, with in-person workdays Tuesday-Thursday at our Tampa office.

As part of the Advanced Analytics team, you will:

• Support team members in daily analytics functions, including data querying, data preparation/manipulation, and exploratory data analysis.
• Contribute to multiple analytics projects, which may include:
• Test design and analysis
• Ad-hoc analytical requests
• Development of proof-of-concept models
• Evaluation of variables for modeling purposes
• Explore and apply artificial intelligence and generative AI tools to support analytics workflows, including data exploration, coding, research, documentation, and analytical proof-of-concept development.
• Apply statistical and machine learning approaches to business problems and evaluate model performance using appropriate analytical techniques.
• Evaluate the effectiveness, limitations, and appropriate use of AI-assisted approaches, with attention to accuracy, data quality, privacy, and responsible AI practices.
• Apply academic learning to real-world business problems in a professional environment.
• Build a foundational understanding of New York Life Direct's business and analytics capabilities.
• Participate in professional development workshops, networking events, and team-building activities.
• Engage with senior professionals through fireside chats and structured networking opportunities.
• Be considered for a potential full-time role after graduation.

By the end of the internship, you will have:

• A basic understanding of NYLD's business related to the project areas you support.
• A foundational understanding of NYLD's analytics database infrastructure.
• Completed several low- to moderate-complexity data tasks in support of assigned analytics projects.
• Successfully delivered 1-2 medium- to high-priority analytical projects under manager supervision.
• Developed practical experience using modern AI and analytics tools appropriately within a professional data science environment.
• Presented insights through influential presentations and discussions, including:
• At least one midpoint presentation
• One final presentation
• Received positive feedback from business stakeholders on the majority of presentations.

You bring strong communication skills, intellectual curiosity, and a desire to learn and grow in a data-driven environment. You are comfortable working with data, thinking analytically, collaborating with others to solve complex problems, and learning new analytical and AI-enabled tools. You demonstrate sound judgment when evaluating analytical results and are interested in understanding both the opportunities…