2027 Guardian Summer MBA Associate, Business Transformation at Guardian in New York, NY

Job description

Our 2027 Summer Internship Program is a paid 10-week learning experience where you will be immersed in the daily environment of a thriving global financial services company. You will gain invaluable industry and organizational knowledge through daily business interactions and job assignments, in addition to engaging in projects that directly affect our business, interacting with senior leaders, and networking with employees and interns across our offices. This 10-week internship provides you with realistic experiences and information of what it is like to work at Guardian. The Team: This internship sits within the Business Transformation organization for FPRS (Financial Protection and Retirement Solutions), the team accountable for how Guardian's Life, Disability, and Annuity businesses set strategy into motion. We own enterprise portfolio planning and prioritization, lead multi-year value stream transformation across Purchase, Underwriting, and Service, and drive the AI enablement agenda that is reshaping how our colleagues work. You will be placed against one of two assignments based on business priority at the time of hire and your own interests: Assignment A: Portfolio Planning & Strategic Investment Support the 2028 annual planning cycle, the process by which FPRS decides where to invest hundreds of millions of dollars across technology, operations, and growth initiatives. You will help build and pressure-test business cases, size initiatives, model trade-offs, and prepare the materials that senior leaders use to make funding decisions. You will do this work with AI in the loop, using generative AI assistants and AI-enabled analytics tools (Microsoft 365 Copilot, Excel Copilot, Power BI, Tableau) to accelerate modeling, scenario analysis, and research synthesis while applying your own judgment to the recommendation. Assignment B: AI Enablement & Adoption Support Guardian’s AI enablement agenda across FPRS as both a practitioner and a change agent. You will apply structured use-case prioritization frameworks to identify high-value AI opportunities, quantify productivity and value capture, define and track adoption metrics, design prompts and AI-assisted workflows, and build the enablement assets and training that help thousands of colleagues adopt AI tools in their daily work. You will also contribute to how we govern responsible AI use in a regulated financial services environment. Internship Dates: The internship program will run from Thursday, May 27, 2027- Friday, August 6, 2027 . We review applications on a rolling basis, and we encourage you to apply as soon as you are ready. You are: A first-year MBA student (graduating between December 2027-June 2028), who is proactive, comfortable with ambiguity, able to listen and make quick decisions, and thrives in a goal-oriented environment Energized by the intersection of business strategy and AI, and you see AI as a tool that amplifies human judgment rather than replaces it Location (Housing is not provided): New York, NY (in office 3x a week) You have: Required Qualifications: Strong problem-solving skills and business acumen, with the ability to structure ambiguous problems and drive to a defensible recommendation Proficiency with both qualitative and quantitative analysis, including comfort building financial models, sizing opportunities, and working with imperfect data Demonstrated project leadership potential, including prioritization of workstreams and collaboration with cross-functional colleagues Excellent written and verbal communication skills, and advanced proficiency with Microsoft Excel and PowerPoint, including their AI-enabled features (Excel Copilot, PowerPoint Designer) Genuine curiosity about AI and emerging technology, and an interest in how it changes the way work gets done Hands-on experience using generative AI tools (such as ChatGPT, Claude, Copilot, or Gemini) for business problems, including prompt design and the ability to iterate with a model to g