Senior Data Analyst - Trust, Safety, and Fraud Analytics

Who we are:  At Rover, pets and their people are at the heart of everything we do. We connect pet parents with trusted pet care across the U.S., Canada, Europe, and Australia. Headquartered in Seattle and Barcelona, we’re a values driven, fast-growing tech company focused on building safe and personalized experiences tailored to the needs of each unique pet. We’re investing in AI as a business accelerator and provide every team member access to AI tools in service of creating better experiences for our community. We are proud to be recognized as a great place to work, having been named among the 100 Best Companies to Work For in Seattle Business Magazine and Washington’s Best Workplaces in the Puget Sound Business Journal. At Rover we’re committed to creating an accessible, inclusive, and welcoming community, which starts with our employees. Want to make an impact? Join our pack and come work (and play!) with us. *This is a hybrid position that has the minimum expectation to work out of our Downtown Seattle Office two days per week on Mondays and Thursdays. For this reason, candidates must be based in the Greater Seattle Area or willing to relocate. Additionally, applicants must be currently authorized to work in the United States on a full-time basis, without the need for current or future employer sponsorship for an employment-based visa status. Who we're looking for: We are seeking a Senior Data Analyst to partner closely with Rover’s Infosec team and Trust and Safety Leadership team, driving initiatives that make Rover a safer community for pet parents and sitters. This is a high-visibility role where you will collaborate directly with a diverse set of stakeholders to define, measure, and improve the success of Rover’s Fraud program. You will be responsible for conducting in-depth analysis of new and developing fraud trends, which includes proactively identifying issues and then developing and proposing actionable solutions. This role requires a unique skillset: the ideal candidate must be comfortable translating ambiguous business problems into crisp requirements, and then using those to build creative data products that meet niche business needs. You should be a natural builder - someone who is passionate about starting from ground zero and building a highly effective analytical program with relative autonomy.