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Senior Data Analyst, GTM

Tremendous·US·United States·senior
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Tremendous is the fast, free, flexible way to send bulk payouts to people in over 230 countries and regions. 20,000+ companies ranging from mom-and-pops to Google, MIT, and United Way have sent over $1 billion, saving 15 hours a month on average. In both our product and our workplace, we’re intentional about making work more efficient, flexible, and fulfilling. Tremendous is a fully remote, high-documentation, low-meeting culture, which means more time for what matters in both your professional and personal life. Our customers, who include marketers, researchers, HR teams, and nonprofits, rave about how quick and easy it is to use Tremendous — check the ratings on G2 https://www.g2.com/products/tremendous/reviews. Yet there’s a lot of complexity under the hood, including over 2,500 redemption options and plenty of banking infrastructure. This duality makes working here a fun challenge. Tremendous is profitable and growing without outside investors. Join us before our next international offsite. About the role We are hiring an experienced data analyst to partner across our go-to-market teams (Sales, RevOps, Marketing, and Customer Success) and connect the full revenue funnel from acquisition through retention. Tremendous values data as a first-class citizen and believes insights unlock significant growth. You will collaborate closely with the data team and company-wide stakeholders. As we continue to grow the business, you will scale GTM-focused insights and lead new data-driven initiatives. What you'll do - Apply a range of analytics methods to gain insights across our go-to-market teams (sales, RevOps, marketing, and customer success), such as conversion funnels and attribution. - Consolidate diverse facts and findings into compelling narratives that can be applied across Tremendous. - Advocate for data-informed decisions by partnering with key stakeholders and senior leaders. - Identify and implement improvements within the Data team by standardizing processes, de