Financial & Deal Analyst, Reinsurance & MGA (AI-First)

What You'll Do

• Turn raw broker submissions into clean, decision-ready packages: digest decks, loss runs, exposure data, and exhibits into something the team can act on quickly.
• Build the financial models used to evaluate deals: premium, expected loss, expenses, collateral, downside scenarios, and underwriting margin.
• Rebuild the numbers from source. Flag where an assumption looks soft, information is missing, or a deal could break, and bring it to the team rather than taking any figure on face value.
• Draft deal memos, broker emails, diligence requests, internal summaries, board materials, and contract comment trackers.
• Support contract review and program buildout: reinsurance terms, collateral and reporting provisions, claims provisions, fronting carrier diligence, reinsurer materials, underwriting guidelines, and exposure tracking.
• Run the deal pipeline so nothing slips: status, deadlines, dependencies, open questions, and next steps.
• Own the knowledge base and document flow so the team operates from a single source of truth.
• Use AI tools such as ChatGPT, Claude, and Excel to move faster on analysis, drafting, and research, then verify the output before it is used.

Who You Are

• Hightly analytical, quantitatively strong, and comfortable with financial logic.
• Strong in Excel and able to build clean, auditable models.
• Clear, concise, and effective writer.
• Highly driven, proactive, and comfortable taking ownership of ambiguous problems.
• Able to learn technical concepts quickly and ask good questions.
• Organized enough to keep multiple live workstreams moving at once.
• Able to form a view from incomplete information and show your assumptions clearly, while understanding that final underwriting and capital decisions are made by senior leadership.
• Detail-oriented without losing the commercial big picture.
• Discreet with confidential and market-sensitive information.
• AI-native, but not AI-dependent: you use AI tools to move faster, and you verify before anything goes out.

Background

• 1-5 years of analytical experience preferred; an exceptional early-career candidate with the right horsepower will be considered.
• Strong quantitative degree or equivalent demonstrated analytical ability (finance, economics, actuarial science, statistics, applied mathematics, engineering, operations research, data science, computer science, or related).
• Strong Excel and financial modeling skills, and excellent written communication, are required.
• Exposure to insurance, reinsurance, MGA/program business, finance, credit risk, banking, consulting, or analytics is helpful but not required.
• Python, SQL, Power BI, Claude Code, Codex, GitHub Copilot, or workflow-automation experience is a plus.