Strategy & Analytics Manager — Travel Supply & AI (100% Remote - USA)

Hopper•Washington, DC

20h•$160,000 - $200,000•Remote

About The Position

Hopper is hiring a Strategy & Analytics Manager to own the analytical and operational infrastructure powering its Travel Commercial organisation. This team is responsible for all hotel, home, and car inventory distributed to global partners. This is a hands-on builder role at the intersection of data, process, and technology, working closely with Product and Engineering and reporting into senior commercial leadership.

Requirements

2+ years of experience in data analytics, sales operations, strategy & operations, or a similar analytical or commercial role.
Proficiency in SQL and hands-on experience with BI and data tools such as Looker, Tableau, or BigQuery.
A track record of building things (data models, dashboards, process frameworks, operational tools).
Strong commercial instincts paired with rigorous analytical capability.
Genuine excitement about AI and an existing habit of using it to accelerate and improve work.
Experience working cross-functionally with Product and/or Engineering teams, with sufficient technical fluency.
First-principles thinking.
A bias for action, a strong sense of ownership, and the ability to thrive in fast-moving, ambiguous environments.

Responsibilities

Design, build, and maintain data models, dashboards, and reporting frameworks for commercial visibility.
Use AI tools in the analytical workflow to accelerate insight generation and improve output quality.
Run deep-dive analytical projects to identify patterns, anomalies, and opportunities in commercial data, translating findings into actionable recommendations.
Define and track KPIs for business outcomes and process effectiveness.
Own preparation and follow-through for key internal meetings, strategic reviews, and cross-functional forums.
Build analytical frameworks for quarterly planning, forecasting, and target-setting.
Map, challenge, and rebuild core commercial workflows (pipeline management, forecasting, sales incentives) for efficiency and scalability.
Implement operational improvements end-to-end, driving adoption and measuring impact.
Identify opportunities for AI to fundamentally change commercial processes and deploy solutions.
Develop a hands-on understanding of the commercial tech stack to identify friction points and missed opportunities.
Translate commercial problems into briefs for Product and Engineering teams, maintaining technical fluency.
Leverage AI-driven tools to assist in efficiently reviewing applications.