Staff Product Analyst, Operations

You bring a first-principles mindset to messy operational questions and don't wait to be handed a fully-scoped problem — you find the signal in the noise and drive toward an answer. You're comfortable moving between rigorous statistical thinking and practical, ship-it analysis, and you want a seat where your work directly shapes how a growing company understands its own cost drivers. If you're energized by ambiguity, curious about applying data science techniques to real operational levers, and want to grow your career at the intersection of analytics and AI-enabled tooling, this role was built with you in mind.

You'll own the analytical backbone of Hover's Operations function, working to understand what actually drives turnaround time (TAT) across our property-scan review computer vision pipeline. That means designing and running experiments and statistical models to isolate the real impact of process changes — including proprietary techniques Hover has already shipped to make our BPO partners' jobs easier. You'll build the reporting, alerting, and tooling that tells the team when and how each part of the ops pipeline is being used, so decisions are made on evidence, not guesswork. You'll work cross-functionally with Operations, Finance, and Analytics Engineering to bring a sharper, more scientific lens to how Hover measures and improves its operations, and you'll have real latitude to develop your own point of view and advocate for it.

• Design and run statistical analyses and experiments to identify true drivers of operational turnaround time
• Build and maintain reporting and alerting systems that give the team visibility into tool usage and process health across the ops pipeline
• Partner closely with Operations, Finance, and Analytics Engineering to translate findings into action
• Develop an independent point of view on what's driving cost and efficiency, and advocate for it with data
• Lean into AI-enabled tooling and automation to scale the impact of analytics work over time

• 7+ years of experience in a data analyst, analytics, or operations research role, ideally within a fast-paced operational or marketplace environment
• Strong SQL and Python skills, with the ability to move fluidly from ad hoc analysis to production-quality reporting
• Experience with statistical modeling or experimentation (A/B testing, causal inference, or similar) to isolate the drivers of a business outcome
• Comfort working with BI tooling to build dashboards and reporting that others rely on
• A first-principles approach to problem-solving — you dig into the "why" rather than accepting the first plausible explanation
• Demonstrated ability to work autonomously, develop an independent analytical point of view, and communicate it persuasively to stakeholders
• Strong cross-functional collaboration skills, with experience partnering across Operations, Finance, or similar functions

• Experience or coursework in data science techniques (causal inference, machine learning fundamentals) beyond core analytics
• Background at a high-growth operational company (e.g., logistics, marketplace, or on-demand services)

Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.

The US base salary range for this full-time position is $172,000-$212,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

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