Senior Data Analyst, Strategic Operations

Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.

Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.

You will own the architecture and buildout of Collective's Operations Intelligence Warehouse: the BigQuery data layer and Metabase BI that make throughput, quality, variance, and capacity inspectable across an AI-native financial operation. You will also own the analytics on top of it: spotting trends before they become problems, surfacing the signal leadership acts on, and seeing around corners with evidence rather than instinct. The AI in an AI-native financial services firm is only as good as the operation it learns from, and the operation is only as good as the data that describes it. That data layer is yours.

You will join Strategic Operations, the applied operations research team that designs how Collective's member delivery engine runs. Reporting to the Head of Strategic Operations, you will lead the design of our operational data, set the modeling and quality standards the team builds on, and turn raw production-line telemetry into the operating metrics and insights the business runs on: cycle time, first-pass yield, utilization, and cost-to-serve.

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• Python for analysis and pipeline work.

• Exposure to statistical process control, six sigma, or industrial engineering methods.

• Experience instrumenting AI agent or workflow telemetry, or supporting LLM eval programs.

• AI-assisted, low-code development experience (Claude Code, AppSheet, or similar).