2027 New York Life Direct Summer Internship Program - AI & DS

New York Life Insurance•Tampa, FL

13d•Hybrid

About The Position

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. Role Overview 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.

Requirements

Currently enrolled in and pursuing a graduate degree in a technical or quantitative field such as: Data Science, Statistics, Mathematics, Economics, Computer Science, Business Analytics, Or a related quantitative discipline
Basic proficiency in SQL and a statistical programming language such as Python or R.
Experience with data querying, data preparation, exploratory data analysis, statistical modeling, or machine learning through coursework, research, internships, or project work.
Ability to critically evaluate analytical and AI-generated outputs for accuracy, appropriateness, and limitations.
Strong written and verbal communication skills, intellectual curiosity, and demonstrated ability to collaborate effectively.
Demonstrated leadership or meaningful contribution to academic, campus, professional, or community activities.
To be eligible for this program, you must be authorized to work in the U.S. We do not offer any type of employment-based immigration sponsorship for this program. Likewise, this program is not available to those authorized to work under optional practical training (OPT) or curricular practical training (CPT).

Nice To Haves

Coursework or project experience in statistics, including regression modeling and/or design of experiments, preferred.
Familiarity with modern AI or generative AI tools and experience using them for analytical, coding, research, or academic project work is preferred.
Experience with cloud-based analytics environments such as AWS is a plus.

Responsibilities

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.