Data Analyst - Economic Insights & Communications

At Stripe, a Most Loved Workplace® certified employer in the Financial Services space, Economic infrastructure for the internet, powering ambitious businesses globally..

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<h2><strong>Who we are</strong></h2>

<h3><strong>About Stripe</strong></h3>

<p>Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.</p>

<h3><strong>About the team</strong></h3>

<p>We’re looking for an experienced data analyst to deepen understanding around the economic impact Stripe is having globally. You will be part of a community of analysts and data scientists on the Go-to-Market Analytics team, and you will partner with Stripe’s Communications teams to build and protect Stripe’s brand and influence across the world. </p>

<h2><strong>What you’ll do</strong></h2>

<p>This person will bridge Economic Insights and how we Communicate them with the broader public. Stripe has a unique view of the world, with real-time insight into changing trends, industries, and cross-border commerce. The Data Analyst, Economic Insights & Communication role will focus on constructing and analyzing data, built upon robust data pipelines and a strong data architecture, to demonstrate how Stripe enables broad and often surprising economic growth. This role will help tease out novel economic insights from Stripe data to tell stories about how pockets of the economy are evolving, and how Stripe is advancing economic opportunity and increasing the GDP of the internet.</p>

<h3><strong>Responsibilities</strong></h3>

<ul>

<li>Partner with the Communications teams to imagine, scope, and lead research projects that bring to life different facets of Stripe’s economic impact </li>

<li>Publish findings both internally and externally</li>

<li>Generate hypotheses, rapidly test them against Stripe data, and proactively share the most interesting nuggets</li>

<li>Design, implement and maintain data pipelines and dashboards to generate insights from Stripe internal and external public data sources</li>

<li>Define and monitor key economic impact metrics</li>

<li>Go deep on understanding business drivers, user segments, cohorts and macroeconomic trends</li>

<li>Partner closely with Communications teams to identify and analyze key trends and produce social posts, blogs, reports, briefings and campaign content leveraging Stripe data</li>

</ul>

<h2><strong>Who you are</strong></h2>

<p>We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.</p>

<h3><strong>Minimum requirements</strong></h3>

<ul>

<li>3+ years of experience in analytical roles working with large datasets</li>

<li>Bachelor’s degree in Statistics, Economics, Mathematics, Engineering, Sciences or a related quantitative field</li>

<li>Proficiency in SQL and Python and experience building and maintaining data pipelines using a distributed data framework</li>

<li>Experience building self-serve dashboards or other scalable analytical tools for partner teams</li>

<li>Experience developing data-informed narratives and visualizations for external publication</li>

</ul>

<h3><strong>Preferred qualifications</strong></h3>

<ul>

<li>Master’s degree in Statistics, Economics, Mathematics, Engineering, Sciences or a related quantitative field and/or experience in working on data analytics in the tech field</li>

<li>Experience working with institutions that are respected by policymakers and the wider public for their economic insight</li>

<li>Familiarity with survey design and analysis</li>

</ul>

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