- Location
- Austin, Texas, United States · published
- Type
- Full-time
- Source
- Workable
Description
We’re building the most loved men's retailer on the planet and inspiring and equipping adventurers near and far. Scaling that vision takes grit, curiosity, and smarter, faster ways of operating.
As our Business Analyst – AI & Automation, you’ll embed within Strategic Finance to champion internal AI adoption and turn real operational friction into high-leverage solutions. This is an early-career seat built for a curious analytical thinker ready to bridge the gap between commercial strategy and modern tooling. It is not software engineering, and it is not a traditional financial reporting desk.
You’ll partner across Planning, Merchandising, E-commerce, Growth, and Operations to unpack complex problems, collaborate with Data & Tech on technical specs when needed, and roll up your sleeves to own the execution: analysis, rapid prototyping, building, testing, validation, and iteration.
Bring the analytical horsepower and the drive to build - we’ll provide the launchpad to shape a career at the intersection of strategy, data, and technology.
This role is based out of our headquarters in Austin, TX; relocation support will be provided for remote hires.
Responsibilities
- Help build, test, and improve analytical tools used to make real business decisions across Planning, Merchandising, Buying, E-commerce, Operations, and Growth
- Use SQL, BigQuery, Hex, and AI tools to analyze data, turn it into actionable insights, prototype solutions, and automate manual workflows
- Work cross-functionally to understand how decisions are made today and where better tooling can create leverage
- Translate business questions into clear analytical requirements and partner with Data & Tech when deeper architecture or production support is required
- Build prototypes and internal tools, validate outputs against actual business results, and iterate based on user feedback so the output stays actionable
- Pressure-test AI-generated work rather than treating AI output as inherently correct
- Document assumptions, logic, and business rules so that tools can be understood, trusted, and maintained by others
- Help move successful prototypes from an idea into something teams actually use