FM Innovation Summer Intern (AI, Data & Venture Exploration)

FM•Providence, RI

About The Position

FM Innovation is seeking a highly motivated intern to work at the intersection of business processes, data, and AI. This role is ideal for a candidate who is curious about how large organizations operate—and how emerging technologies like machine learning and LLMs can transform workflows, decision-making, and product innovation. You will collaborate with multiple business units (e.g., Claims, Underwriting, Engineering, Data Analytics) to understand workflows, map data flows, and prototype AI-driven solutions that unlock value from both structured and unstructured data. In parallel, you will contribute to evaluating emerging startups and technologies, helping shape FM’s innovation pipeline and future capabilities.

Requirements

Pursuing a graduate degree in Computer Science, Data Science, Engineering, Business Analytics, or a related field
Strong interest in understanding how businesses operate (processes, workflows, decision systems)
Proficiency in Python and working with data
Familiarity with Machine Learning fundamentals
Familiarity with LLMs / generative AI (prompting, APIs, basic agent concepts)
Strong problem-solving and analytical thinking skills
Excellent communication skills (technical + business)

Nice To Haves

Experience working with both structured data (databases, tables)
Experience working with unstructured data (documents, text, PDFs)
Experience with tools such as Databricks, SQL, APIs
Experience with LLM frameworks or agentic tools (e.g., Claude Code, LangChain, etc.)
Exposure to process mapping, operations, or consulting-style problem solving
Interest in startups, venture ecosystems, or emerging technologies
Experience using Git / version control

Responsibilities

Partner with business stakeholders across FM to map workflows, decision points, and pain points, while analyzing how data—both structured and unstructured—flows across systems to identify inefficiencies, manual steps, and opportunities for automation or augmentation.
Build proofs-of-concept leveraging machine learning models, large language models (LLMs), and hybrid approaches that combine structured datasets with unstructured sources such as reports and notes, developing lightweight tools or agents to extract insights from documents, support decision-making workflows, and automate repetitive knowledge work using both internal and external data sources.
Research and evaluate emerging startups, vendors, and technologies, support pilot initiatives and proof-of-value efforts, and assess product capabilities, differentiation, and strategic fit within FM’s ecosystem, contributing to internal recommendations and executive summaries.
Collaborate across Claims, Underwriting, Engineering, and Data/Platform teams to synthesize technical findings into clear, actionable business insights and present prototypes to stakeholders.
Document workflows, architectures, and outputs, create concise, executive-ready summaries of findings and opportunities, and deliver a final presentation summarizing their work and impact.