Senior Financial Analyst (AI & Automation) - Acquisition & Education

You are AI-native and building-oriented—when a problem lands, your first instinct is to reach for a tool like Claude Code or Codex and build something, not to do it by hand or ask it as a chat question.

You take genuine pride in the state of your numbers: models that are clean, organized, and up-to-date, with the underlying datasets, definitions, and context layers built properly so the same work doesn’t have to be redone next month.

You have solid financial modeling fundamentals—you're strong in Excel and Sheets, you understand how a model should be structured, and that foundation lets you layer automation on top of it with confidence. You can read and interrogate SQL: not necessarily writing every query from scratch, but able to look at what a tool has produced and tell whether it actually answered the question.

You also bring real curiosity—you dig past the first answer without being asked—and real velocity: you know the difference between a question that needs a rigorous, fully-loaded model and one that needs a directional answer fast.

What You'll Do

• Support two different parts of the business at once—our core acquisition motion and our Education business—which means learning two distinct sets of economics and getting exposure most analysts at this level don’t get.
• Own the underlying models for core acquisition: headcount planning, rep productivity, rep compensation, and acquisition forecasting.
• Own the underlying models for Education: order volume, physical product cost and inventory, margin per unit, and ARR.
• Keep those models clean, current, and well-structured—model hygiene is a core part of the job, not housekeeping around the edges.
• Work with analytics to build the foundational datasets, definitions, and context layers that let analysis be automated and repeated quickly rather than rebuilt by hand each cycle.
• Build automated workflows using AI coding tools—automating model refreshes, data pulls, and recurring analysis so the team's reporting runs itself as much as possible.
• Independently pull and validate the data you need via SQL and Redshift, using AI tools and our context layer, with ad hoc asks to Analytics for the harder or more detailed requests.
• Build and maintain self-serve dashboards for both areas so recurring questions stop being asked manually.
• Proactively flag data quality issues, methodology gaps, or reporting inconsistencies before they become someone else's problem to catch.

What You've Done

• 4+ years of experience in Strategic Finance, investment banking, or a similar field.
• Read, dissected, and diagnosed SQL queries—you don’t need to write every query from scratch, but you must be able to look at a query (including one an AI wrote) and judge whether it answered the question correctly. This is a must-have.
• Reached for AI coding tools (Claude Code, Codex, or similar) as your default way of solving problems day to day—building, automating, and iterating routinely, not as a one-off experiment, and not just using the chat interface.
• Built Excel or Sheets-based financial models confidently and often—and increasingly used AI tools to build them faster, with the modeling fundamentals to know when the output is wrong.
• Owned a recurring financial or operational report end-to-end—not just updated someone else's template, but understood and improved the underlying logic.
• Kept a set of models or datasets clean and current over time, with the definitions and structure to make them reusable.
• Operated in a fast-moving, ambiguous environment where the question changed before the last answer was even finished.
• Effective communication style with the ability to work cross-functionally outside of finance teams and proactive communication with teammates.